Showing 200 of total 2429 results (show query)
dgbonett
statpsych:Statistical Methods for Psychologists
Implements confidence interval and sample size methods that are especially useful in psychological research. The methods can be applied in 1-group, 2-group, paired-samples, and multiple-group designs and to a variety of parameters including means, medians, proportions, slopes, standardized mean differences, standardized linear contrasts of means, plus several measures of correlation and association. Confidence interval and sample size functions are given for single parameters as well as differences, ratios, and linear contrasts of parameters. The sample size functions can be used to approximate the sample size needed to estimate a parameter or function of parameters with desired confidence interval precision or to perform a variety of hypothesis tests (directional two-sided, equivalence, superiority, noninferiority) with desired power. For details see: Statistical Methods for Psychologists, Volumes 1 – 4, <https://dgbonett.sites.ucsc.edu/>.
Maintained by Douglas G. Bonett. Last updated 3 months ago.
251.4 match 6 stars 4.83 score 15 scripts 1 dependentseasystats
effectsize:Indices of Effect Size
Provide utilities to work with indices of effect size for a wide variety of models and hypothesis tests (see list of supported models using the function 'insight::supported_models()'), allowing computation of and conversion between indices such as Cohen's d, r, odds, etc. References: Ben-Shachar et al. (2020) <doi:10.21105/joss.02815>.
Maintained by Mattan S. Ben-Shachar. Last updated 1 months ago.
anovacohens-dcomputeconversioncorrelationeffect-sizeeffectsizehacktoberfesthedges-ginterpretationstandardizationstandardizedstatistics
69.9 match 344 stars 16.38 score 1.8k scripts 29 dependentsbioc
ComplexHeatmap:Make Complex Heatmaps
Complex heatmaps are efficient to visualize associations between different sources of data sets and reveal potential patterns. Here the ComplexHeatmap package provides a highly flexible way to arrange multiple heatmaps and supports various annotation graphics.
Maintained by Zuguang Gu. Last updated 5 months ago.
softwarevisualizationsequencingclusteringcomplex-heatmapsheatmap
35.4 match 1.3k stars 16.93 score 16k scripts 151 dependentsdetlew
PowerTOST:Power and Sample Size for (Bio)Equivalence Studies
Contains functions to calculate power and sample size for various study designs used in bioequivalence studies. Use known.designs() to see the designs supported. Power and sample size can be obtained based on different methods, amongst them prominently the TOST procedure (two one-sided t-tests). See README and NEWS for further information.
Maintained by Detlew Labes. Last updated 1 years ago.
56.3 match 20 stars 9.10 score 112 scripts 4 dependentscran
epiR:Tools for the Analysis of Epidemiological Data
Tools for the analysis of epidemiological and surveillance data. Contains functions for directly and indirectly adjusting measures of disease frequency, quantifying measures of association on the basis of single or multiple strata of count data presented in a contingency table, computation of confidence intervals around incidence risk and incidence rate estimates and sample size calculations for cross-sectional, case-control and cohort studies. Surveillance tools include functions to calculate an appropriate sample size for 1- and 2-stage representative freedom surveys, functions to estimate surveillance system sensitivity and functions to support scenario tree modelling analyses.
Maintained by Mark Stevenson. Last updated 2 months ago.
58.6 match 10 stars 8.18 score 10 dependentscorentinjgosling
metaConvert:An Automatic Suite for Estimation of Various Effect Size Measures
Automatically estimate 11 effect size measures from a well-formatted dataset. Various other functions can help, for example, removing dependency between several effect sizes, or identifying differences between two datasets. This package is mainly designed to assist in conducting a systematic review with a meta-analysis but can be useful to any researcher interested in estimating an effect size.
Maintained by Corentin J. Gosling. Last updated 4 months ago.
118.4 match 3.48 score 3 scripts 1 dependentssizespectrum
mizer:Dynamic Multi-Species Size Spectrum Modelling
A set of classes and methods to set up and run multi-species, trait based and community size spectrum ecological models, focused on the marine environment.
Maintained by Gustav Delius. Last updated 2 months ago.
ecosystem-modelfish-population-dynamicsfisheriesfisheries-managementmarine-ecosystempopulation-dynamicssimulationsize-structurespecies-interactionstransport-equationcpp
42.7 match 38 stars 9.43 score 207 scriptstiledb-inc
tiledb:Modern Database Engine for Complex Data Based on Multi-Dimensional Arrays
The modern database 'TileDB' introduces a powerful on-disk format for storing and accessing any complex data based on multi-dimensional arrays. It supports dense and sparse arrays, dataframes and key-values stores, cloud storage ('S3', 'GCS', 'Azure'), chunked arrays, multiple compression, encryption and checksum filters, uses a fully multi-threaded implementation, supports parallel I/O, data versioning ('time travel'), metadata and groups. It is implemented as an embeddable cross-platform C++ library with APIs from several languages, and integrations. This package provides the R support.
Maintained by Isaiah Norton. Last updated 6 days ago.
arrayhdfss3storage-managertiledbcpp
28.1 match 107 stars 11.96 score 306 scripts 4 dependentsalexkowa
EnvStats:Package for Environmental Statistics, Including US EPA Guidance
Graphical and statistical analyses of environmental data, with focus on analyzing chemical concentrations and physical parameters, usually in the context of mandated environmental monitoring. Major environmental statistical methods found in the literature and regulatory guidance documents, with extensive help that explains what these methods do, how to use them, and where to find them in the literature. Numerous built-in data sets from regulatory guidance documents and environmental statistics literature. Includes scripts reproducing analyses presented in the book "EnvStats: An R Package for Environmental Statistics" (Millard, 2013, Springer, ISBN 978-1-4614-8455-4, <doi:10.1007/978-1-4614-8456-1>).
Maintained by Alexander Kowarik. Last updated 18 days ago.
25.2 match 26 stars 12.80 score 2.4k scripts 46 dependentshopkinsidd
phylosamp:Sample Size Calculations for Molecular and Phylogenetic Studies
Implements novel tools for estimating sample sizes needed for phylogenetic studies, including studies focused on estimating the probability of true pathogen transmission between two cases given phylogenetic linkage and studies focused on tracking pathogen variants at a population level. Methods described in Wohl, Giles, and Lessler (2021) and in Wohl, Lee, DiPrete, and Lessler (2023).
Maintained by Justin Lessler. Last updated 2 years ago.
48.1 match 12 stars 6.65 score 25 scriptsigraph
igraph:Network Analysis and Visualization
Routines for simple graphs and network analysis. It can handle large graphs very well and provides functions for generating random and regular graphs, graph visualization, centrality methods and much more.
Maintained by Kirill Müller. Last updated 6 hours ago.
complex-networksgraph-algorithmsgraph-theorymathematicsnetwork-analysisnetwork-graphfortranlibxml2glpkopenblascpp
14.9 match 583 stars 21.10 score 31k scripts 1.9k dependentsctu-bern
presize:Precision Based Sample Size Calculation
Bland (2009) <doi:10.1136/bmj.b3985> recommended to base study sizes on the width of the confidence interval rather the power of a statistical test. The goal of 'presize' is to provide functions for such precision based sample size calculations. For a given sample size, the functions will return the precision (width of the confidence interval), and vice versa.
Maintained by Alan G. Haynes. Last updated 5 months ago.
confidence-intervalsprecisionsample-size-calculationshiny-app
39.6 match 17 stars 7.22 score 36 scripts 1 dependentsbioc
RCy3:Functions to Access and Control Cytoscape
Vizualize, analyze and explore networks using Cytoscape via R. Anything you can do using the graphical user interface of Cytoscape, you can now do with a single RCy3 function.
Maintained by Alex Pico. Last updated 5 months ago.
visualizationgraphandnetworkthirdpartyclientnetwork
20.2 match 52 stars 13.39 score 628 scripts 15 dependentskeaven
gsDesign:Group Sequential Design
Derives group sequential clinical trial designs and describes their properties. Particular focus on time-to-event, binary, and continuous outcomes. Largely based on methods described in Jennison, Christopher and Turnbull, Bruce W., 2000, "Group Sequential Methods with Applications to Clinical Trials" ISBN: 0-8493-0316-8.
Maintained by Keaven Anderson. Last updated 14 days ago.
biostatisticsboundariesclinical-trialsdesignspending-functions
20.3 match 51 stars 13.05 score 338 scripts 5 dependentscran
PracTools:Designing and Weighting Survey Samples
Functions and datasets to support Valliant, Dever, and Kreuter (2018), <doi:10.1007/978-3-319-93632-1>, "Practical Tools for Designing and Weighting Survey Samples". Contains functions for sample size calculation for survey samples using stratified or clustered one-, two-, and three-stage sample designs, and single-stage audit sample designs. Functions are included that will group geographic units accounting for distances apart and measures of size. Other functions compute variance components for multistage designs and sample sizes in two-phase designs. A number of example data sets are included.
Maintained by Richard Valliant. Last updated 9 months ago.
58.4 match 1 stars 4.48 score 101 scripts 1 dependentschrisaberson
pwr2ppl:Power Analyses for Common Designs (Power to the People)
Statistical power analysis for designs including t-tests, correlations, multiple regression, ANOVA, mediation, and logistic regression. Functions accompany Aberson (2019) <doi:10.4324/9781315171500>.
Maintained by Chris Aberson. Last updated 3 years ago.
58.9 match 17 stars 4.16 score 17 scriptsiandryden
shapes:Statistical Shape Analysis
Routines for the statistical analysis of landmark shapes, including Procrustes analysis, graphical displays, principal components analysis, permutation and bootstrap tests, thin-plate spline transformation grids and comparing covariance matrices. See Dryden, I.L. and Mardia, K.V. (2016). Statistical shape analysis, with Applications in R (2nd Edition), John Wiley and Sons.
Maintained by Ian Dryden. Last updated 4 months ago.
27.4 match 7 stars 8.50 score 225 scripts 24 dependentsheliosdrm
pwr:Basic Functions for Power Analysis
Power analysis functions along the lines of Cohen (1988).
Maintained by Helios De Rosario. Last updated 1 years ago.
17.8 match 105 stars 12.97 score 2.6k scripts 28 dependentsstan-dev
posterior:Tools for Working with Posterior Distributions
Provides useful tools for both users and developers of packages for fitting Bayesian models or working with output from Bayesian models. The primary goals of the package are to: (a) Efficiently convert between many different useful formats of draws (samples) from posterior or prior distributions. (b) Provide consistent methods for operations commonly performed on draws, for example, subsetting, binding, or mutating draws. (c) Provide various summaries of draws in convenient formats. (d) Provide lightweight implementations of state of the art posterior inference diagnostics. References: Vehtari et al. (2021) <doi:10.1214/20-BA1221>.
Maintained by Paul-Christian Bürkner. Last updated 12 days ago.
13.9 match 168 stars 16.13 score 3.3k scripts 342 dependentsr-lib
vctrs:Vector Helpers
Defines new notions of prototype and size that are used to provide tools for consistent and well-founded type-coercion and size-recycling, and are in turn connected to ideas of type- and size-stability useful for analysing function interfaces.
Maintained by Davis Vaughan. Last updated 5 months ago.
11.5 match 290 stars 18.97 score 1.1k scripts 13k dependentsbioc
igvR:igvR: integrative genomics viewer
Access to igv.js, the Integrative Genomics Viewer running in a web browser.
Maintained by Arkadiusz Gladki. Last updated 5 months ago.
visualizationthirdpartyclientgenomebrowsers
26.0 match 43 stars 8.31 score 118 scriptsbioc
rhdf5:R Interface to HDF5
This package provides an interface between HDF5 and R. HDF5's main features are the ability to store and access very large and/or complex datasets and a wide variety of metadata on mass storage (disk) through a completely portable file format. The rhdf5 package is thus suited for the exchange of large and/or complex datasets between R and other software package, and for letting R applications work on datasets that are larger than the available RAM.
Maintained by Mike Smith. Last updated 2 months ago.
infrastructuredataimporthdf5rhdf5opensslcurlzlibcpp
13.5 match 62 stars 15.93 score 4.2k scripts 232 dependentsmikewlcheung
metaSEM:Meta-Analysis using Structural Equation Modeling
A collection of functions for conducting meta-analysis using a structural equation modeling (SEM) approach via the 'OpenMx' and 'lavaan' packages. It also implements various procedures to perform meta-analytic structural equation modeling on the correlation and covariance matrices, see Cheung (2015) <doi:10.3389/fpsyg.2014.01521>.
Maintained by Mike Cheung. Last updated 11 days ago.
meta-analysismeta-analytic-semmissing-datamultilevel-modelsmultivariate-analysisstructural-equation-modelingstructural-equation-models
22.4 match 30 stars 9.43 score 208 scripts 1 dependentsshixiangwang
sigminer:Extract, Analyze and Visualize Mutational Signatures for Genomic Variations
Genomic alterations including single nucleotide substitution, copy number alteration, etc. are the major force for cancer initialization and development. Due to the specificity of molecular lesions caused by genomic alterations, we can generate characteristic alteration spectra, called 'signature' (Wang, Shixiang, et al. (2021) <DOI:10.1371/journal.pgen.1009557> & Alexandrov, Ludmil B., et al. (2020) <DOI:10.1038/s41586-020-1943-3> & Steele Christopher D., et al. (2022) <DOI:10.1038/s41586-022-04738-6>). This package helps users to extract, analyze and visualize signatures from genomic alteration records, thus providing new insight into cancer study.
Maintained by Shixiang Wang. Last updated 5 months ago.
bayesian-nmfbioinformaticscancer-researchcnvcopynumber-signaturescosmic-signaturesdbseasy-to-useindelmutational-signaturesnmfnmf-extractionsbssignature-extractionsomatic-mutationssomatic-variantsvisualizationcpp
22.0 match 150 stars 9.48 score 123 scripts 2 dependentspsirusteam
samplesize4surveys:Sample Size Calculations for Complex Surveys
Computes the required sample size for estimation of totals, means and proportions under complex sampling designs.
Maintained by Hugo Andres Gutierrez Rojas. Last updated 5 years ago.
40.4 match 2 stars 4.78 score 60 scriptssmartdata-analysis-and-statistics
SimTOST:Sample Size Estimation for Bio-Equivalence Trials Through Simulation
Sample size estimation for bio-equivalence trials is supported through a simulation-based approach that extends the Two One-Sided Tests (TOST) procedure. The methodology provides flexibility in hypothesis testing, accommodates multiple treatment comparisons, and accounts for correlated endpoints. Users can model complex trial scenarios, including parallel and crossover designs, intra-subject variability, and different equivalence margins. Monte Carlo simulations enable accurate estimation of power and type I error rates, ensuring well-calibrated study designs. The statistical framework builds on established methods for equivalence testing and multiple hypothesis testing in bio-equivalence studies, as described in Schuirmann (1987) <doi:10.1007/BF01068419>, Mielke et al. (2018) <doi:10.1080/19466315.2017.1371071>, Shieh (2022) <doi:10.1371/journal.pone.0269128>, and Sozu et al. (2015) <doi:10.1007/978-3-319-22005-5>. Comprehensive documentation and vignettes guide users through implementation and interpretation of results.
Maintained by Thomas Debray. Last updated 28 days ago.
mcmcmulti-armmultiple-comparisonssample-size-calculationsample-size-estimationtrial-simulationopenblascpp
29.0 match 2 stars 6.47 score 7 scriptsjinghuazhao
gap:Genetic Analysis Package
As first reported [Zhao, J. H. 2007. "gap: Genetic Analysis Package". J Stat Soft 23(8):1-18. <doi:10.18637/jss.v023.i08>], it is designed as an integrated package for genetic data analysis of both population and family data. Currently, it contains functions for sample size calculations of both population-based and family-based designs, probability of familial disease aggregation, kinship calculation, statistics in linkage analysis, and association analysis involving genetic markers including haplotype analysis with or without environmental covariates. Over years, the package has been developed in-between many projects hence also in line with the name (gap).
Maintained by Jing Hua Zhao. Last updated 18 days ago.
14.7 match 12 stars 11.88 score 448 scripts 16 dependentscvxgrp
CVXR:Disciplined Convex Optimization
An object-oriented modeling language for disciplined convex programming (DCP) as described in Fu, Narasimhan, and Boyd (2020, <doi:10.18637/jss.v094.i14>). It allows the user to formulate convex optimization problems in a natural way following mathematical convention and DCP rules. The system analyzes the problem, verifies its convexity, converts it into a canonical form, and hands it off to an appropriate solver to obtain the solution. Interfaces to solvers on CRAN and elsewhere are provided, both commercial and open source.
Maintained by Anqi Fu. Last updated 4 months ago.
13.1 match 207 stars 12.89 score 768 scripts 51 dependentsepiverse-trace
finalsize:Calculate the Final Size of an Epidemic
Calculate the final size of a susceptible-infectious-recovered epidemic in a population with demographic variation in contact patterns and susceptibility to disease, as discussed in Miller (2012) <doi:10.1007/s11538-012-9749-6>.
Maintained by Rosalind Eggo. Last updated 1 months ago.
epidemic-modellingepidemiologyepiverseoutbreak-analysisrcppsdg-3cpp
20.6 match 11 stars 8.11 score 46 scriptsbioc
cfDNAPro:cfDNAPro extracts and Visualises biological features from whole genome sequencing data of cell-free DNA
cfDNA fragments carry important features for building cancer sample classification ML models, such as fragment size, and fragment end motif etc. Analyzing and visualizing fragment size metrics, as well as other biological features in a curated, standardized, scalable, well-documented, and reproducible way might be time intensive. This package intends to resolve these problems and simplify the process. It offers two sets of functions for cfDNA feature characterization and visualization.
Maintained by Haichao Wang. Last updated 5 months ago.
visualizationsequencingwholegenomebioinformaticscancer-genomicscancer-researchcell-free-dnaearly-detectiongenomics-visualizationliquid-biopsyswgswhole-genome-sequencing
27.1 match 28 stars 6.04 score 13 scriptsthaiserf
forImage:Foraminiferal Image Analysis and Test Measurement
The goal of this collection of functions is to provide an easy to use tool for the measurement of foraminifera and other unicellulars organisms size. With functions developed to guide foraminiferal test biovolume calculations and cell biomass estimations. The volume function includes several microalgae models geometric adaptations based on Hillebrand et al. (1999) <doi:10.1046/j.1529-8817.1999.3520403.x>, Sun and Liu (2003) <doi:10.1093/plankt/fbg096> and Vadrucci, Cabrini and Basset (2007) <doi:10.1285/i1825229Xv1n2p83>.
Maintained by Thaise R Freitas. Last updated 4 years ago.
60.5 match 2.70 score 2 scriptsalexanderlynl
safestats:Safe Anytime-Valid Inference
Functions to design and apply tests that are anytime valid. The functions can be used to design hypothesis tests in the prospective/randomised control trial setting or in the observational/retrospective setting. The resulting tests remain valid under both optional stopping and optional continuation. The current version includes safe t-tests and safe tests of two proportions. For details on the theory of safe tests, see Grunwald, de Heide and Koolen (2019) "Safe Testing" <arXiv:1906.07801>, for details on safe logrank tests see ter Schure, Perez-Ortiz, Ly and Grunwald (2020) "The Safe Logrank Test: Error Control under Continuous Monitoring with Unlimited Horizon" <arXiv:2011.06931v3> and Turner, Ly and Grunwald (2021) "Safe Tests and Always-Valid Confidence Intervals for contingency tables and beyond" <arXiv:2106.02693> for details on safe contingency table tests.
Maintained by Alexander Ly. Last updated 2 years ago.
evalueshacktoberfestsafe-testingstatistics
30.9 match 6 stars 5.23 score 14 scriptspsirusteam
TeachingSampling:Selection of Samples and Parameter Estimation in Finite Population
Allows the user to draw probabilistic samples and make inferences from a finite population based on several sampling designs.
Maintained by Hugo Andres Gutierrez Rojas. Last updated 5 years ago.
27.2 match 4 stars 5.80 score 217 scripts 4 dependentskassambara
rstatix:Pipe-Friendly Framework for Basic Statistical Tests
Provides a simple and intuitive pipe-friendly framework, coherent with the 'tidyverse' design philosophy, for performing basic statistical tests, including t-test, Wilcoxon test, ANOVA, Kruskal-Wallis and correlation analyses. The output of each test is automatically transformed into a tidy data frame to facilitate visualization. Additional functions are available for reshaping, reordering, manipulating and visualizing correlation matrix. Functions are also included to facilitate the analysis of factorial experiments, including purely 'within-Ss' designs (repeated measures), purely 'between-Ss' designs, and mixed 'within-and-between-Ss' designs. It's also possible to compute several effect size metrics, including "eta squared" for ANOVA, "Cohen's d" for t-test and 'Cramer V' for the association between categorical variables. The package contains helper functions for identifying univariate and multivariate outliers, assessing normality and homogeneity of variances.
Maintained by Alboukadel Kassambara. Last updated 2 years ago.
9.8 match 456 stars 15.16 score 11k scripts 420 dependentsmrcieu
TwoSampleMR:Two Sample MR Functions and Interface to MRC Integrative Epidemiology Unit OpenGWAS Database
A package for performing Mendelian randomization using GWAS summary data. It uses the IEU OpenGWAS database <https://gwas.mrcieu.ac.uk/> to automatically obtain data, and a wide range of methods to run the analysis.
Maintained by Gibran Hemani. Last updated 12 days ago.
13.1 match 467 stars 11.23 score 1.7k scripts 1 dependentsalanarnholt
BSDA:Basic Statistics and Data Analysis
Data sets for book "Basic Statistics and Data Analysis" by Larry J. Kitchens.
Maintained by Alan T. Arnholt. Last updated 2 years ago.
15.9 match 7 stars 9.11 score 1.3k scripts 6 dependentsrobinhankin
permutations:The Symmetric Group: Permutations of a Finite Set
Manipulates invertible functions from a finite set to itself. Can transform from word form to cycle form and back. To cite the package in publications please use Hankin (2020) "Introducing the permutations R package", SoftwareX, volume 11 <doi:10.1016/j.softx.2020.100453>.
Maintained by Robin K. S. Hankin. Last updated 1 months ago.
17.2 match 6 stars 8.23 score 49 scripts 2 dependentslhdjung
scrutiny:Error Detection in Science
Test published summary statistics for consistency (Brown and Heathers, 2017, <doi:10.1177/1948550616673876>; Allard, 2018, <https://aurelienallard.netlify.app/post/anaytic-grimmer-possibility-standard-deviations/>; Heathers and Brown, 2019, <https://osf.io/5vb3u/>). The package also provides infrastructure for implementing new error detection techniques.
Maintained by Lukas Jung. Last updated 6 months ago.
21.6 match 8 stars 6.52 score 38 scriptsycphs
openxlsx:Read, Write and Edit xlsx Files
Simplifies the creation of Excel .xlsx files by providing a high level interface to writing, styling and editing worksheets. Through the use of 'Rcpp', read/write times are comparable to the 'xlsx' and 'XLConnect' packages with the added benefit of removing the dependency on Java.
Maintained by Jan Marvin Garbuszus. Last updated 2 months ago.
7.4 match 232 stars 18.98 score 20k scripts 270 dependentsdvats
mcmcse:Monte Carlo Standard Errors for MCMC
Provides tools for computing Monte Carlo standard errors (MCSE) in Markov chain Monte Carlo (MCMC) settings. MCSE computation for expectation and quantile estimators is supported as well as multivariate estimations. The package also provides functions for computing effective sample size and for plotting Monte Carlo estimates versus sample size.
Maintained by Dootika Vats. Last updated 1 months ago.
effective-sample-sizemcmcoutput-aopenblascpp
15.8 match 12 stars 8.77 score 314 scripts 17 dependentsr-forge
Sleuth3:Data Sets from Ramsey and Schafer's "Statistical Sleuth (3rd Ed)"
Data sets from Ramsey, F.L. and Schafer, D.W. (2013), "The Statistical Sleuth: A Course in Methods of Data Analysis (3rd ed)", Cengage Learning.
Maintained by Berwin A Turlach. Last updated 1 years ago.
21.4 match 6.38 score 522 scriptsjepusto
SingleCaseES:A Calculator for Single-Case Effect Sizes
Provides R functions for calculating basic effect size indices for single-case designs, including several non-overlap measures and parametric effect size measures, and for estimating the gradual effects model developed by Swan and Pustejovsky (2018) <DOI:10.1080/00273171.2018.1466681>. Standard errors and confidence intervals (based on the assumption that the outcome measurements are mutually independent) are provided for the subset of effect sizes indices with known sampling distributions.
Maintained by James E. Pustejovsky. Last updated 6 months ago.
19.3 match 7 stars 6.87 score 41 scripts 1 dependentspegeler
samplesizeCMH:Power and Sample Size Calculation for the Cochran-Mantel-Haenszel Test
Calculates the power and sample size for Cochran-Mantel-Haenszel tests. There are also several helper functions for working with probability, odds, relative risk, and odds ratio values.
Maintained by Paul Egeler. Last updated 1 months ago.
categorical-datacmh-testsample-sizestatistical-powerstatistics
21.8 match 4 stars 5.94 score 36 scriptsmtorchiano
effsize:Efficient Effect Size Computation
A collection of functions to compute the standardized effect sizes for experiments (Cohen d, Hedges g, Cliff delta, Vargha-Delaney A). The computation algorithms have been optimized to allow efficient computation even with very large data sets.
Maintained by Marco Torchiano. Last updated 3 years ago.
11.0 match 104 stars 11.62 score 1.6k scripts 15 dependentshaozhu233
kableExtra:Construct Complex Table with 'kable' and Pipe Syntax
Build complex HTML or 'LaTeX' tables using 'kable()' from 'knitr' and the piping syntax from 'magrittr'. Function 'kable()' is a light weight table generator coming from 'knitr'. This package simplifies the way to manipulate the HTML or 'LaTeX' codes generated by 'kable()' and allows users to construct complex tables and customize styles using a readable syntax.
Maintained by Hao Zhu. Last updated 12 days ago.
htmlkablekableextraknitrlatexrmarkdown
6.5 match 702 stars 19.35 score 55k scripts 163 dependentsgeomorphr
geomorph:Geometric Morphometric Analyses of 2D and 3D Landmark Data
Read, manipulate, and digitize landmark data, generate shape variables via Procrustes analysis for points, curves and surfaces, perform shape analyses, and provide graphical depictions of shapes and patterns of shape variation.
Maintained by Dean Adams. Last updated 1 months ago.
10.5 match 76 stars 12.05 score 700 scripts 6 dependentsramnathv
htmlwidgets:HTML Widgets for R
A framework for creating HTML widgets that render in various contexts including the R console, 'R Markdown' documents, and 'Shiny' web applications.
Maintained by Carson Sievert. Last updated 1 years ago.
6.5 match 791 stars 19.05 score 7.4k scripts 3.1k dependentspsychmeta
psychmeta:Psychometric Meta-Analysis Toolkit
Tools for computing bare-bones and psychometric meta-analyses and for generating psychometric data for use in meta-analysis simulations. Supports bare-bones, individual-correction, and artifact-distribution methods for meta-analyzing correlations and d values. Includes tools for converting effect sizes, computing sporadic artifact corrections, reshaping meta-analytic databases, computing multivariate corrections for range variation, and more. Bugs can be reported to <https://github.com/psychmeta/psychmeta/issues> or <issues@psychmeta.com>.
Maintained by Jeffrey A. Dahlke. Last updated 9 months ago.
hacktoberfestmeta-analysispsychologypsychometricpsychometrics
15.0 match 57 stars 8.25 score 151 scriptsmiddleton-lab
abd:The Analysis of Biological Data
The abd package contains data sets and sample code for The Analysis of Biological Data by Michael Whitlock and Dolph Schluter (2009; Roberts & Company Publishers).
Maintained by Kevin M. Middleton. Last updated 11 months ago.
22.3 match 6 stars 5.53 score 182 scripts 1 dependentsr-forge
Sleuth2:Data Sets from Ramsey and Schafer's "Statistical Sleuth (2nd Ed)"
Data sets from Ramsey, F.L. and Schafer, D.W. (2002), "The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed)", Duxbury.
Maintained by Berwin A Turlach. Last updated 1 years ago.
21.4 match 5.70 score 191 scriptsmerck
gsDesign2:Group Sequential Design with Non-Constant Effect
The goal of 'gsDesign2' is to enable fixed or group sequential design under non-proportional hazards. To enable highly flexible enrollment, time-to-event and time-to-dropout assumptions, 'gsDesign2' offers piecewise constant enrollment, failure rates, and dropout rates for a stratified population. This package includes three methods for designs: average hazard ratio, weighted logrank tests in Yung and Liu (2019) <doi:10.1111/biom.13196>, and MaxCombo tests. Substantial flexibility on top of what is in the 'gsDesign' package is intended for selecting boundaries.
Maintained by Yujie Zhao. Last updated 18 hours ago.
13.4 match 22 stars 8.92 score 186 scriptswviechtb
metafor:Meta-Analysis Package for R
A comprehensive collection of functions for conducting meta-analyses in R. The package includes functions to calculate various effect sizes or outcome measures, fit equal-, fixed-, random-, and mixed-effects models to such data, carry out moderator and meta-regression analyses, and create various types of meta-analytical plots (e.g., forest, funnel, radial, L'Abbe, Baujat, bubble, and GOSH plots). For meta-analyses of binomial and person-time data, the package also provides functions that implement specialized methods, including the Mantel-Haenszel method, Peto's method, and a variety of suitable generalized linear (mixed-effects) models (i.e., mixed-effects logistic and Poisson regression models). Finally, the package provides functionality for fitting meta-analytic multivariate/multilevel models that account for non-independent sampling errors and/or true effects (e.g., due to the inclusion of multiple treatment studies, multiple endpoints, or other forms of clustering). Network meta-analyses and meta-analyses accounting for known correlation structures (e.g., due to phylogenetic relatedness) can also be conducted. An introduction to the package can be found in Viechtbauer (2010) <doi:10.18637/jss.v036.i03>.
Maintained by Wolfgang Viechtbauer. Last updated 3 days ago.
meta-analysismixed-effectsmultilevel-modelsmultivariate
7.3 match 246 stars 16.30 score 4.9k scripts 92 dependentseddelbuettel
RProtoBuf:R Interface to the 'Protocol Buffers' 'API' (Version 2 or 3)
Protocol Buffers are a way of encoding structured data in an efficient yet extensible format. Google uses Protocol Buffers for almost all of its internal 'RPC' protocols and file formats. Additional documentation is available in two included vignettes one of which corresponds to our 'JSS' paper (2016, <doi:10.18637/jss.v071.i02>. A sufficiently recent version of 'Protocol Buffers' library is required; currently version 3.3.0 from 2017 is the stated minimum.
Maintained by Dirk Eddelbuettel. Last updated 2 days ago.
c-plus-plusprotocol-buffersprotobufcpp
10.3 match 73 stars 11.44 score 126 scripts 21 dependentsmoderndive
moderndive:Tidyverse-Friendly Introductory Linear Regression
Datasets and wrapper functions for tidyverse-friendly introductory linear regression, used in "Statistical Inference via Data Science: A ModernDive into R and the Tidyverse" available at <https://moderndive.com/>.
Maintained by Albert Y. Kim. Last updated 3 months ago.
10.4 match 88 stars 11.35 score 1.8k scriptsrpact-com
rpact:Confirmatory Adaptive Clinical Trial Design and Analysis
Design and analysis of confirmatory adaptive clinical trials with continuous, binary, and survival endpoints according to the methods described in the monograph by Wassmer and Brannath (2016) <doi:10.1007/978-3-319-32562-0>. This includes classical group sequential as well as multi-stage adaptive hypotheses tests that are based on the combination testing principle.
Maintained by Friedrich Pahlke. Last updated 12 days ago.
adaptive-designanalysisclinical-trialscount-datagroup-sequential-designspower-calculationsample-size-calculationsimulationvalidatedfortrancpp
14.2 match 25 stars 7.98 score 110 scripts 1 dependentscran
sae:Small Area Estimation
Functions for small area estimation.
Maintained by Yolanda Marhuenda. Last updated 5 years ago.
20.2 match 6 stars 5.49 score 83 scripts 8 dependentsindrajeetpatil
ggstatsplot:'ggplot2' Based Plots with Statistical Details
Extension of 'ggplot2', 'ggstatsplot' creates graphics with details from statistical tests included in the plots themselves. It provides an easier syntax to generate information-rich plots for statistical analysis of continuous (violin plots, scatterplots, histograms, dot plots, dot-and-whisker plots) or categorical (pie and bar charts) data. Currently, it supports the most common types of statistical approaches and tests: parametric, nonparametric, robust, and Bayesian versions of t-test/ANOVA, correlation analyses, contingency table analysis, meta-analysis, and regression analyses. References: Patil (2021) <doi:10.21105/joss.03236>.
Maintained by Indrajeet Patil. Last updated 22 days ago.
bayes-factorsdatasciencedatavizeffect-sizeggplot-extensionhypothesis-testingnon-parametric-statisticsregression-modelsstatistical-analysis
7.5 match 2.1k stars 14.49 score 3.0k scripts 1 dependentsweiliang
powerMediation:Power/Sample Size Calculation for Mediation Analysis
Functions to calculate power and sample size for testing (1) mediation effects; (2) the slope in a simple linear regression; (3) odds ratio in a simple logistic regression; (4) mean change for longitudinal study with 2 time points; (5) interaction effect in 2-way ANOVA; and (6) the slope in a simple Poisson regression.
Maintained by Weiliang Qiu. Last updated 4 years ago.
26.7 match 3 stars 3.97 score 65 scripts 2 dependentsmcdonohue
longpower:Sample Size Calculations for Longitudinal Data
Compute power and sample size for linear models of longitudinal data. Supported models include mixed-effects models and models fit by generalized least squares and generalized estimating equations. The package is described in Iddi and Donohue (2022) <DOI:10.32614/RJ-2022-022>. Relevant formulas are derived by Liu and Liang (1997) <DOI:10.2307/2533554>, Diggle et al (2002) <ISBN:9780199676750>, and Lu, Luo, and Chen (2008) <DOI:10.2202/1557-4679.1098>.
Maintained by Michael C. Donohue. Last updated 7 months ago.
17.1 match 3 stars 6.04 score 22 scripts 1 dependentsharrelfe
Hmisc:Harrell Miscellaneous
Contains many functions useful for data analysis, high-level graphics, utility operations, functions for computing sample size and power, simulation, importing and annotating datasets, imputing missing values, advanced table making, variable clustering, character string manipulation, conversion of R objects to LaTeX and html code, recoding variables, caching, simplified parallel computing, encrypting and decrypting data using a safe workflow, general moving window statistical estimation, and assistance in interpreting principal component analysis.
Maintained by Frank E Harrell Jr. Last updated 2 days ago.
5.8 match 210 stars 17.61 score 17k scripts 750 dependentsbioc
topconfects:Top Confident Effect Sizes
Rank results by confident effect sizes, while maintaining False Discovery Rate and False Coverage-statement Rate control. Topconfects is an alternative presentation of TREAT results with improved usability, eliminating p-values and instead providing confidence bounds. The main application is differential gene expression analysis, providing genes ranked in order of confident log2 fold change, but it can be applied to any collection of effect sizes with associated standard errors.
Maintained by Paul Harrison. Last updated 3 months ago.
geneexpressiondifferentialexpressiontranscriptomicsrnaseqmrnamicroarrayregressionmultiplecomparison
13.7 match 14 stars 7.38 score 18 scripts 2 dependentsropensci
gigs:Assess Fetal, Newborn, and Child Growth with International Standards
Convert between anthropometric measures and z-scores/centiles in multiple growth standards, and classify fetal, newborn, and child growth accordingly. With a simple interface to growth standards from the World Health Organisation and International Fetal and Newborn Growth Consortium for the 21st Century, gigs makes growth assessment easy and reproducible for clinicians, researchers and policy-makers.
Maintained by Simon R Parker. Last updated 27 days ago.
anthropometrygrowth-standardsintergrowthwho
23.1 match 4 stars 4.38 score 8 scriptsdoomlab
MOTE:Effect Size and Confidence Interval Calculator
Measure of the Effect ('MOTE') is an effect size calculator, including a wide variety of effect sizes in the mean differences family (all versions of d) and the variance overlap family (eta, omega, epsilon, r). 'MOTE' provides non-central confidence intervals for each effect size, relevant test statistics, and output for reporting in APA Style (American Psychological Association, 2010, <ISBN:1433805618>) with 'LaTeX'. In research, an over-reliance on p-values may conceal the fact that a study is under-powered (Halsey, Curran-Everett, Vowler, & Drummond, 2015 <doi:10.1038/nmeth.3288>). A test may be statistically significant, yet practically inconsequential (Fritz, Scherndl, & Kühberger, 2012 <doi:10.1177/0959354312436870>). Although the American Psychological Association has long advocated for the inclusion of effect sizes (Wilkinson & American Psychological Association Task Force on Statistical Inference, 1999 <doi:10.1037/0003-066X.54.8.594>), the vast majority of peer-reviewed, published academic studies stop short of reporting effect sizes and confidence intervals (Cumming, 2013, <doi:10.1177/0956797613504966>). 'MOTE' simplifies the use and interpretation of effect sizes and confidence intervals. For more information, visit <https://www.aggieerin.com/shiny-server>.
Maintained by Erin M. Buchanan. Last updated 3 years ago.
confidenceeffectintervalsizestatistics
15.0 match 17 stars 6.69 score 320 scripts 1 dependentsjeffreyevans
spatialEco:Spatial Analysis and Modelling Utilities
Utilities to support spatial data manipulation, query, sampling and modelling in ecological applications. Functions include models for species population density, spatial smoothing, multivariate separability, point process model for creating pseudo- absences and sub-sampling, Quadrant-based sampling and analysis, auto-logistic modeling, sampling models, cluster optimization, statistical exploratory tools and raster-based metrics.
Maintained by Jeffrey S. Evans. Last updated 15 days ago.
biodiversityconservationecologyr-spatialrasterspatialvector
10.1 match 110 stars 9.55 score 736 scripts 2 dependentsallisonhorst
palmerpenguins:Palmer Archipelago (Antarctica) Penguin Data
Size measurements, clutch observations, and blood isotope ratios for adult foraging Adélie, Chinstrap, and Gentoo penguins observed on islands in the Palmer Archipelago near Palmer Station, Antarctica. Data were collected and made available by Dr. Kristen Gorman and the Palmer Station Long Term Ecological Research (LTER) Program.
Maintained by Allison Horst. Last updated 6 months ago.
7.1 match 928 stars 13.30 score 11k scripts 52 dependentsejosymart
sizeMat:Estimate Size at Sexual Maturity
Estimate morphometric and gonadal size at sexual maturity for organisms, usually fish and invertebrates. It includes methods for classification based on relative growth (using principal components analysis, hierarchical clustering, discriminant analysis), logistic regression (Frequentist or Bayes), parameters estimation and some basic plots.
Maintained by Josymar Torrejon-Magallanes. Last updated 1 years ago.
allometric-variablesgonad-maturitymorphometric-maturity
20.0 match 4 stars 4.72 score 26 scriptsidem-lab
conmat:Builds Contact Matrices using GAMs and Population Data
Builds contact matrices using GAMs and population data. This package incorporates data that is copyright Commonwealth of Australia (Australian Electoral Commission and Australian Bureau of Statistics) 2020.
Maintained by Nicholas Tierney. Last updated 8 days ago.
contact-matricesinfectious-diseasespopulation-datapublic-health
13.1 match 19 stars 7.21 score 47 scriptsweiliang
powerSurvEpi:Power and Sample Size Calculation for Survival Analysis of Epidemiological Studies
Functions to calculate power and sample size for testing main effect or interaction effect in the survival analysis of epidemiological studies (non-randomized studies), taking into account the correlation between the covariate of the interest and other covariates. Some calculations also take into account the competing risks and stratified analysis. This package also includes a set of functions to calculate power and sample size for testing main effect in the survival analysis of randomized clinical trials and conditional logistic regression for nested case-control study.
Maintained by Weiliang Qiu. Last updated 4 years ago.
25.3 match 3.72 score 77 scripts 2 dependentswviechtb
metadat:Meta-Analysis Datasets
A collection of meta-analysis datasets for teaching purposes, illustrating/testing meta-analytic methods, and validating published analyses.
Maintained by Wolfgang Viechtbauer. Last updated 4 days ago.
8.9 match 30 stars 10.54 score 65 scripts 93 dependentsrstudio
keras3:R Interface to 'Keras'
Interface to 'Keras' <https://keras.io>, a high-level neural networks API. 'Keras' was developed with a focus on enabling fast experimentation, supports both convolution based networks and recurrent networks (as well as combinations of the two), and runs seamlessly on both CPU and GPU devices.
Maintained by Tomasz Kalinowski. Last updated 2 days ago.
6.9 match 845 stars 13.60 score 264 scripts 2 dependentsagi-lab
SynthETIC:Synthetic Experience Tracking Insurance Claims
Creation of an individual claims simulator which generates various features of non-life insurance claims. An initial set of test parameters, designed to mirror the experience of an Auto Liability portfolio, were set up and applied by default to generate a realistic test data set of individual claims (see vignette). The simulated data set then allows practitioners to back-test the validity of various reserving models and to prove and/or disprove certain actuarial assumptions made in claims modelling. The distributional assumptions used to generate this data set can be easily modified by users to match their experiences. Reference: Avanzi B, Taylor G, Wang M, Wong B (2020) "SynthETIC: an individual insurance claim simulator with feature control" <arXiv:2008.05693>.
Maintained by Melantha Wang. Last updated 1 years ago.
14.9 match 12 stars 6.22 score 23 scripts 2 dependentssimsem
semTools:Useful Tools for Structural Equation Modeling
Provides miscellaneous tools for structural equation modeling, many of which extend the 'lavaan' package. For example, latent interactions can be estimated using product indicators (Lin et al., 2010, <doi:10.1080/10705511.2010.488999>) and simple effects probed; analytical power analyses can be conducted (Jak et al., 2021, <doi:10.3758/s13428-020-01479-0>); and scale reliability can be estimated based on estimated factor-model parameters.
Maintained by Terrence D. Jorgensen. Last updated 5 days ago.
6.7 match 79 stars 13.74 score 1.1k scripts 31 dependentsdwarton
ecostats:Code and Data Accompanying the Eco-Stats Text (Warton 2022)
Functions and data supporting the Eco-Stats text (Warton, 2022, Springer), and solutions to exercises. Functions include tools for using simulation envelopes in diagnostic plots, and a function for diagnostic plots of multivariate linear models. Datasets mentioned in the package are included here (where not available elsewhere) and there is a vignette for each chapter of the text with solutions to exercises.
Maintained by David Warton. Last updated 1 years ago.
13.8 match 8 stars 6.58 score 53 scriptsemmanuelparadis
ape:Analyses of Phylogenetics and Evolution
Functions for reading, writing, plotting, and manipulating phylogenetic trees, analyses of comparative data in a phylogenetic framework, ancestral character analyses, analyses of diversification and macroevolution, computing distances from DNA sequences, reading and writing nucleotide sequences as well as importing from BioConductor, and several tools such as Mantel's test, generalized skyline plots, graphical exploration of phylogenetic data (alex, trex, kronoviz), estimation of absolute evolutionary rates and clock-like trees using mean path lengths and penalized likelihood, dating trees with non-contemporaneous sequences, translating DNA into AA sequences, and assessing sequence alignments. Phylogeny estimation can be done with the NJ, BIONJ, ME, MVR, SDM, and triangle methods, and several methods handling incomplete distance matrices (NJ*, BIONJ*, MVR*, and the corresponding triangle method). Some functions call external applications (PhyML, Clustal, T-Coffee, Muscle) whose results are returned into R.
Maintained by Emmanuel Paradis. Last updated 2 days ago.
5.3 match 64 stars 17.22 score 13k scripts 599 dependentsacclab
dabestr:Data Analysis using Bootstrap-Coupled Estimation
Data Analysis using Bootstrap-Coupled ESTimation. Estimation statistics is a simple framework that avoids the pitfalls of significance testing. It uses familiar statistical concepts: means, mean differences, and error bars. More importantly, it focuses on the effect size of one's experiment/intervention, as opposed to a false dichotomy engendered by P values. An estimation plot has two key features: 1. It presents all datapoints as a swarmplot, which orders each point to display the underlying distribution. 2. It presents the effect size as a bootstrap 95% confidence interval on a separate but aligned axes. Estimation plots are introduced in Ho et al., Nature Methods 2019, 1548-7105. <doi:10.1038/s41592-019-0470-3>. The free-to-view PDF is located at <https://www.nature.com/articles/s41592-019-0470-3.epdf?author_access_token=Euy6APITxsYA3huBKOFBvNRgN0jAjWel9jnR3ZoTv0Pr6zJiJ3AA5aH4989gOJS_dajtNr1Wt17D0fh-t4GFcvqwMYN03qb8C33na_UrCUcGrt-Z0J9aPL6TPSbOxIC-pbHWKUDo2XsUOr3hQmlRew%3D%3D>.
Maintained by Yishan Mai. Last updated 1 years ago.
data-analysisdata-visualizationestimationstatistics
9.2 match 214 stars 9.80 score 142 scriptsbioc
scuttle:Single-Cell RNA-Seq Analysis Utilities
Provides basic utility functions for performing single-cell analyses, focusing on simple normalization, quality control and data transformations. Also provides some helper functions to assist development of other packages.
Maintained by Aaron Lun. Last updated 5 months ago.
immunooncologysinglecellrnaseqqualitycontrolpreprocessingnormalizationtranscriptomicsgeneexpressionsequencingsoftwaredataimportopenblascpp
8.7 match 10.21 score 1.7k scripts 80 dependentsrspatial
terra:Spatial Data Analysis
Methods for spatial data analysis with vector (points, lines, polygons) and raster (grid) data. Methods for vector data include geometric operations such as intersect and buffer. Raster methods include local, focal, global, zonal and geometric operations. The predict and interpolate methods facilitate the use of regression type (interpolation, machine learning) models for spatial prediction, including with satellite remote sensing data. Processing of very large files is supported. See the manual and tutorials on <https://rspatial.org/> to get started. 'terra' replaces the 'raster' package ('terra' can do more, and it is faster and easier to use).
Maintained by Robert J. Hijmans. Last updated 8 hours ago.
geospatialrasterspatialvectoronetbbprojgdalgeoscpp
5.0 match 559 stars 17.63 score 17k scripts 851 dependentsopenpharma
DoseFinding:Planning and Analyzing Dose Finding Experiments
The DoseFinding package provides functions for the design and analysis of dose-finding experiments (with focus on pharmaceutical Phase II clinical trials). It provides functions for: multiple contrast tests, fitting non-linear dose-response models (using Bayesian and non-Bayesian estimation), calculating optimal designs and an implementation of the MCPMod methodology (Pinheiro et al. (2014) <doi:10.1002/sim.6052>).
Maintained by Marius Thomas. Last updated 1 days ago.
8.5 match 8 stars 10.38 score 98 scripts 10 dependentsmarkmfredrickson
optmatch:Functions for Optimal Matching
Distance based bipartite matching using minimum cost flow, oriented to matching of treatment and control groups in observational studies ('Hansen' and 'Klopfer' 2006 <doi:10.1198/106186006X137047>). Routines are provided to generate distances from generalised linear models (propensity score matching), formulas giving variables on which to limit matched distances, stratified or exact matching directives, or calipers, alone or in combination.
Maintained by Josh Errickson. Last updated 3 months ago.
7.2 match 47 stars 12.22 score 588 scripts 5 dependentskrassowski
ComplexUpset:Create Complex UpSet Plots Using 'ggplot2' Components
UpSet plots are an improvement over Venn Diagram for set overlap visualizations. Striving to bring the best of the 'UpSetR' and 'ggplot2', this package offers a way to create complex overlap visualisations, using simple and familiar tools, i.e. geoms of 'ggplot2'. For introduction to UpSet concept, see Lex et al. (2014) <doi:10.1109/TVCG.2014.2346248>.
Maintained by Michał Krassowski. Last updated 1 years ago.
ggplotggplot2patchworkpythonrstatupsetupsetrvennvenn-diagramvisualization
9.0 match 491 stars 9.54 score 554 scripts 4 dependentsrvlenth
emmeans:Estimated Marginal Means, aka Least-Squares Means
Obtain estimated marginal means (EMMs) for many linear, generalized linear, and mixed models. Compute contrasts or linear functions of EMMs, trends, and comparisons of slopes. Plots and other displays. Least-squares means are discussed, and the term "estimated marginal means" is suggested, in Searle, Speed, and Milliken (1980) Population marginal means in the linear model: An alternative to least squares means, The American Statistician 34(4), 216-221 <doi:10.1080/00031305.1980.10483031>.
Maintained by Russell V. Lenth. Last updated 5 days ago.
4.5 match 377 stars 19.19 score 13k scripts 187 dependentsgnelson12
fishmethods:Fishery Science Methods and Models
Functions for applying a wide range of fisheries stock assessment methods.
Maintained by Gary A. Nelson. Last updated 1 months ago.
20.8 match 5 stars 4.12 score 136 scripts 1 dependentsacdelre
compute.es:Compute Effect Sizes
Several functions are available for calculating the most widely used effect sizes (ES), along with their variances, confidence intervals and p-values. The output includes ES's of d (mean difference), g (unbiased estimate of d), r (correlation coefficient), z' (Fisher's z), and OR (odds ratio and log odds ratio). In addition, NNT (number needed to treat), U3, CLES (Common Language Effect Size) and Cliff's Delta are computed. This package uses recommended formulas as described in The Handbook of Research Synthesis and Meta-Analysis (Cooper, Hedges, & Valentine, 2009).
Maintained by AC Del Re. Last updated 5 years ago.
35.0 match 2.44 score 183 scriptsflr
FLasher:Projection and Forecasting of Fish Populations, Stocks and Fleets
Projection of future population and fishery dynamics is carried out for a given set of management targets. A system of equations is solved, using Automatic Differentation (AD), for the levels of effort by fishery (fleet) that will result in the required abundances, catches or fishing mortalities.
Maintained by Iago Mosqueira. Last updated 11 days ago.
12.1 match 2 stars 6.86 score 254 scripts 6 dependentstidyverse
ggplot2:Create Elegant Data Visualisations Using the Grammar of Graphics
A system for 'declaratively' creating graphics, based on "The Grammar of Graphics". You provide the data, tell 'ggplot2' how to map variables to aesthetics, what graphical primitives to use, and it takes care of the details.
Maintained by Thomas Lin Pedersen. Last updated 11 days ago.
data-visualisationvisualisation
3.3 match 6.6k stars 25.10 score 645k scripts 7.5k dependentscran
bda:Binned Data Analysis
Algorithms developed for binned data analysis, gene expression data analysis and measurement error models for ordinal data analysis.
Maintained by Bin Wang. Last updated 7 months ago.
31.1 match 2.61 score 82 scriptsyelleknek
BUCSS:Bias and Uncertainty Corrected Sample Size
Bias- and Uncertainty-Corrected Sample Size. BUCSS implements a method of correcting for publication bias and uncertainty when planning sample sizes in a future study from an original study. See Anderson, Kelley, & Maxwell (2017; Psychological Science, 28, 1547-1562).
Maintained by Ken Kelley. Last updated 5 years ago.
23.0 match 3.51 score 32 scriptsbioc
scDblFinder:scDblFinder
The scDblFinder package gathers various methods for the detection and handling of doublets/multiplets in single-cell sequencing data (i.e. multiple cells captured within the same droplet or reaction volume). It includes methods formerly found in the scran package, the new fast and comprehensive scDblFinder method, and a reimplementation of the Amulet detection method for single-cell ATAC-seq.
Maintained by Pierre-Luc Germain. Last updated 2 months ago.
preprocessingsinglecellrnaseqatacseqdoubletssingle-cell
6.5 match 184 stars 12.34 score 888 scripts 1 dependentsmatteo21q
dani:Design and Analysis of Non-Inferiority Trials
Provides tools to help with the design and analysis of non-inferiority trials. These include functions for doing sample size calculations and for analysing non-inferiority trials, using a variety of outcome types and population-level sumamry measures. It also features functions to make trials more resilient by using the concept of non-inferiority frontiers, as described in Quartagno et al. (2019) <arXiv:1905.00241>. Finally it includes function to design and analyse MAMS-ROCI (aka DURATIONS) trials.
Maintained by Matteo Quartagno. Last updated 7 months ago.
15.0 match 2 stars 5.33 score 27 scriptsimbi-heidelberg
blindrecalc:Blinded Sample Size Recalculation
Computation of key characteristics and plots for blinded sample size recalculation. Continuous as well as binary endpoints are supported in superiority and non-inferiority trials. See Baumann, Pilz, Kieser (2022) <doi:10.32614/RJ-2022-001> for a detailed description. The implemented methods include the approaches by Lu, K. (2019) <doi:10.1002/pst.1737>, Kieser, M. and Friede, T. (2000) <doi:10.1002/(SICI)1097-0258(20000415)19:7%3C901::AID-SIM405%3E3.0.CO;2-L>, Friede, T. and Kieser, M. (2004) <doi:10.1002/pst.140>, Friede, T., Mitchell, C., Mueller-Veltern, G. (2007) <doi:10.1002/bimj.200610373>, and Friede, T. and Kieser, M. (2011) <doi:10.3414/ME09-01-0063>.
Maintained by Lukas Baumann. Last updated 1 years ago.
23.2 match 5 stars 3.40 score 10 scriptsanimint
animint2:Animated Interactive Grammar of Graphics
Functions are provided for defining animated, interactive data visualizations in R code, and rendering on a web page. The 2018 Journal of Computational and Graphical Statistics paper, <doi:10.1080/10618600.2018.1513367> describes the concepts implemented.
Maintained by Toby Hocking. Last updated 29 days ago.
8.9 match 64 stars 8.87 score 173 scriptsmpio-be
rangeMapper:A Platform for the Study of Macro-Ecology of Life History Traits
Tools for generation of (life-history) traits and diversity maps on hexagonal or square grids. Valcu et al.(2012) <doi:10.1111/j.1466-8238.2011.00739.x>.
Maintained by Mihai Valcu. Last updated 2 years ago.
assemblage-levelecologygloballife-history-traitsraster-cellspecies
14.6 match 8 stars 5.38 score 30 scriptsbiomodhub
biomod2:Ensemble Platform for Species Distribution Modeling
Functions for species distribution modeling, calibration and evaluation, ensemble of models, ensemble forecasting and visualization. The package permits to run consistently up to 10 single models on a presence/absences (resp presences/pseudo-absences) dataset and to combine them in ensemble models and ensemble projections. Some bench of other evaluation and visualisation tools are also available within the package.
Maintained by Maya Guéguen. Last updated 1 days ago.
5.6 match 95 stars 13.90 score 536 scripts 7 dependentsstscl
gdverse:Analysis of Spatial Stratified Heterogeneity
Analyzing spatial factors and exploring spatial associations based on the concept of spatial stratified heterogeneity, while also taking into account local spatial dependencies, spatial interpretability, complex spatial interactions, and robust spatial stratification. Additionally, it supports the spatial stratified heterogeneity family established in academic literature.
Maintained by Wenbo Lv. Last updated 4 days ago.
geographical-detectorgeoinformaticsgeospatial-analysisspatial-statisticsspatial-stratified-heterogeneitycpp
8.6 match 32 stars 9.07 score 41 scripts 2 dependentsmihaiconstantin
powerly:Sample Size Analysis for Psychological Networks and More
An implementation of the sample size computation method for network models proposed by Constantin et al. (2021) <doi:10.31234/osf.io/j5v7u>. The implementation takes the form of a three-step recursive algorithm designed to find an optimal sample size given a model specification and a performance measure of interest. It starts with a Monte Carlo simulation step for computing the performance measure and a statistic at various sample sizes selected from an initial sample size range. It continues with a monotone curve-fitting step for interpolating the statistic across the entire sample size range. The final step employs stratified bootstrapping to quantify the uncertainty around the fitted curve.
Maintained by Mihai Constantin. Last updated 2 years ago.
network-modelspower-analysispsychologysample-size-calculation
21.5 match 8 stars 3.60 score 3 scriptsbioc
edgeR:Empirical Analysis of Digital Gene Expression Data in R
Differential expression analysis of sequence count data. Implements a range of statistical methodology based on the negative binomial distributions, including empirical Bayes estimation, exact tests, generalized linear models, quasi-likelihood, and gene set enrichment. Can perform differential analyses of any type of omics data that produces read counts, including RNA-seq, ChIP-seq, ATAC-seq, Bisulfite-seq, SAGE, CAGE, metabolomics, or proteomics spectral counts. RNA-seq analyses can be conducted at the gene or isoform level, and tests can be conducted for differential exon or transcript usage.
Maintained by Yunshun Chen. Last updated 7 days ago.
alternativesplicingbatcheffectbayesianbiomedicalinformaticscellbiologychipseqclusteringcoveragedifferentialexpressiondifferentialmethylationdifferentialsplicingdnamethylationepigeneticsfunctionalgenomicsgeneexpressiongenesetenrichmentgeneticsimmunooncologymultiplecomparisonnormalizationpathwaysproteomicsqualitycontrolregressionrnaseqsagesequencingsinglecellsystemsbiologytimecoursetranscriptiontranscriptomicsopenblas
5.8 match 13.40 score 17k scripts 255 dependentspachadotdev
cpp11armadillo:An 'Armadillo' Interface
Provides function declarations and inline function definitions that facilitate communication between R and the 'Armadillo' 'C++' library for linear algebra and scientific computing. This implementation is detailed in Vargas Sepulveda and Schneider Malamud (2024) <doi:10.48550/arXiv.2408.11074>.
Maintained by Mauricio Vargas Sepulveda. Last updated 27 days ago.
armadillocppcpp11hacktoberfestlinear-algebra
8.4 match 9 stars 9.14 score 1 scripts 16 dependentsbioc
DESeq2:Differential gene expression analysis based on the negative binomial distribution
Estimate variance-mean dependence in count data from high-throughput sequencing assays and test for differential expression based on a model using the negative binomial distribution.
Maintained by Michael Love. Last updated 13 days ago.
sequencingrnaseqchipseqgeneexpressiontranscriptionnormalizationdifferentialexpressionbayesianregressionprincipalcomponentclusteringimmunooncologyopenblascpp
4.8 match 375 stars 16.11 score 17k scripts 115 dependentsbioc
GenomicDistributions:GenomicDistributions: fast analysis of genomic intervals with Bioconductor
If you have a set of genomic ranges, this package can help you with visualization and comparison. It produces several kinds of plots, for example: Chromosome distribution plots, which visualize how your regions are distributed over chromosomes; feature distance distribution plots, which visualizes how your regions are distributed relative to a feature of interest, like Transcription Start Sites (TSSs); genomic partition plots, which visualize how your regions overlap given genomic features such as promoters, introns, exons, or intergenic regions. It also makes it easy to compare one set of ranges to another.
Maintained by Kristyna Kupkova. Last updated 5 months ago.
softwaregenomeannotationgenomeassemblydatarepresentationsequencingcoveragefunctionalgenomicsvisualization
10.2 match 26 stars 7.44 score 25 scriptsaphalo
ggpp:Grammar Extensions to 'ggplot2'
Extensions to 'ggplot2' respecting the grammar of graphics paradigm. Geometries: geom_table(), geom_plot() and geom_grob() add insets to plots using native data coordinates, while geom_table_npc(), geom_plot_npc() and geom_grob_npc() do the same using "npc" coordinates through new aesthetics "npcx" and "npcy". Statistics: select observations based on 2D density. Positions: radial nudging away from a center point and nudging away from a line or curve; combined stacking and nudging; combined dodging and nudging.
Maintained by Pedro J. Aphalo. Last updated 23 days ago.
data-labelsdatavizggplot2-enhancementsggplot2-geomsggplot2-insetsggplot2-positions
6.0 match 130 stars 12.49 score 582 scripts 24 dependentsjulienmoeys
soiltexture:Functions for Soil Texture Plot, Classification and Transformation
"The Soil Texture Wizard" is a set of R functions designed to produce texture triangles (also called texture plots, texture diagrams, texture ternary plots), classify and transform soil textures data. These functions virtually allows to plot any soil texture triangle (classification) into any triangle geometry (isosceles, right-angled triangles, etc.). This set of function is expected to be useful to people using soil textures data from different soil texture classification or different particle size systems. Many (> 15) texture triangles from all around the world are predefined in the package. A simple text based graphical user interface is provided: soiltexture_gui().
Maintained by Julien Moeys. Last updated 1 years ago.
10.5 match 28 stars 7.11 score 136 scripts 1 dependentst-kalinowski
keras:R Interface to 'Keras'
Interface to 'Keras' <https://keras.io>, a high-level neural networks 'API'. 'Keras' was developed with a focus on enabling fast experimentation, supports both convolution based networks and recurrent networks (as well as combinations of the two), and runs seamlessly on both 'CPU' and 'GPU' devices.
Maintained by Tomasz Kalinowski. Last updated 11 months ago.
6.8 match 10.93 score 10k scripts 55 dependentsstocnet
ERPM:Exponential Random Partition Models
Simulates and estimates the Exponential Random Partition Model presented in the paper Hoffman, Block, and Snijders (2023) <doi:10.1177/00811750221145166>. It can also be used to estimate longitudinal partitions, following the model proposed in Hoffman and Chabot (2023) <doi:10.1016/j.socnet.2023.04.002>. The model is an exponential family distribution on the space of partitions (sets of non-overlapping groups) and is called in reference to the Exponential Random Graph Models (ERGM) for networks.
Maintained by Marion Hoffman. Last updated 10 months ago.
15.5 match 10 stars 4.78 scoreklainfo
ScottKnottESD:The Non-Parametric Scott-Knott Effect Size Difference (ESD) Test
The Non-Parametric Scott-Knott Effect Size Difference (ESD) test is a mean comparison approach that leverages a hierarchical clustering to partition the set of treatment means (e.g., means of variable importance scores, means of model performance) into statistically distinct groups with non-negligible difference [Tantithamthavorn et al., (2018) <doi:10.1109/TSE.2018.2794977>].
Maintained by Chakkrit Tantithamthavorn. Last updated 2 years ago.
defect-prediction-modelseffect-sizemultiple-comparisonsranking-algorithmscott-knottstatistical-tests
12.5 match 43 stars 5.77 score 68 scriptscsblatvia
surveyplanning:Survey Planning Tools
Tools for sample survey planning, including sample size calculation, estimation of expected precision for the estimates of totals, and calculation of optimal sample size allocation.
Maintained by Juris Breidaks. Last updated 4 years ago.
15.9 match 8 stars 4.53 score 14 scripts 1 dependentsropensci
BaseSet:Working with Sets the Tidy Way
Implements a class and methods to work with sets, doing intersection, union, complementary sets, power sets, cartesian product and other set operations in a "tidy" way. These set operations are available for both classical sets and fuzzy sets. Import sets from several formats or from other several data structures.
Maintained by Lluís Revilla Sancho. Last updated 28 days ago.
bioconductorbioconductor-packagesets
12.6 match 11 stars 5.69 score 5 scriptsr-forge
distr:Object Oriented Implementation of Distributions
S4-classes and methods for distributions.
Maintained by Peter Ruckdeschel. Last updated 2 months ago.
8.1 match 8.84 score 327 scripts 32 dependentsopenpharma
crmPack:Object-Oriented Implementation of CRM Designs
Implements a wide range of model-based dose escalation designs, ranging from classical and modern continual reassessment methods (CRMs) based on dose-limiting toxicity endpoints to dual-endpoint designs taking into account a biomarker/efficacy outcome. The focus is on Bayesian inference, making it very easy to setup a new design with its own JAGS code. However, it is also possible to implement 3+3 designs for comparison or models with non-Bayesian estimation. The whole package is written in a modular form in the S4 class system, making it very flexible for adaptation to new models, escalation or stopping rules. Further details are presented in Sabanes Bove et al. (2019) <doi:10.18637/jss.v089.i10>.
Maintained by Daniel Sabanes Bove. Last updated 2 months ago.
9.1 match 21 stars 7.79 score 208 scriptselipousson
papersize:Sizing Plots and Files for Paper
A set of convenience functions extending grid, ggplot2, and patchwork to help you size plots and files for printing to paper, postcards, playing cards, and other physical media.
Maintained by Eli Pousson. Last updated 5 months ago.
21.6 match 4 stars 3.26 score 3 scripts 1 dependentsrspatial
raster:Geographic Data Analysis and Modeling
Reading, writing, manipulating, analyzing and modeling of spatial data. This package has been superseded by the "terra" package <https://CRAN.R-project.org/package=terra>.
Maintained by Robert J. Hijmans. Last updated 2 months ago.
4.1 match 164 stars 17.05 score 58k scripts 555 dependentssamch93
BayesRepDesign:Bayesian Design of Replication Studies
Provides functionality for determining the sample size of replication studies using Bayesian design approaches in the normal-normal hierarchical model (Pawel et al., 2023) <doi:10.1037/met0000604>.
Maintained by Samuel Pawel. Last updated 1 years ago.
22.1 match 3 stars 3.18 score 4 scriptspowerandsamplesize
powertools:Power and Sample Size Tools
Power and sample size calculations for a variety of study designs and outcomes. Methods include t tests, ANOVA (including tests for interactions, simple effects and contrasts), proportions, categorical data (chi-square tests and proportional odds), linear, logistic and Poisson regression, alternative and coprimary endpoints, power for confidence intervals, correlation coefficient tests, cluster randomized trials, individually randomized group treatment trials, multisite trials, treatment-by-covariate interaction effects and nonparametric tests of location. Utilities are provided for computing various effect sizes. Companion package to the book "Power and Sample Size in R", Crespi (2025, ISBN:9781138591622).
Maintained by Catherine M. Crespi. Last updated 6 days ago.
19.0 match 3.65 score 9 scriptsmlverse
torchvision:Models, Datasets and Transformations for Images
Provides access to datasets, models and preprocessing facilities for deep learning with images. Integrates seamlessly with the 'torch' package and it's 'API' borrows heavily from 'PyTorch' vision package.
Maintained by Daniel Falbel. Last updated 6 months ago.
7.1 match 65 stars 9.74 score 313 scripts 6 dependentshwborchers
pracma:Practical Numerical Math Functions
Provides a large number of functions from numerical analysis and linear algebra, numerical optimization, differential equations, time series, plus some well-known special mathematical functions. Uses 'MATLAB' function names where appropriate to simplify porting.
Maintained by Hans W. Borchers. Last updated 1 years ago.
5.6 match 29 stars 12.34 score 6.6k scripts 931 dependentsinlabru-org
inlabru:Bayesian Latent Gaussian Modelling using INLA and Extensions
Facilitates spatial and general latent Gaussian modeling using integrated nested Laplace approximation via the INLA package (<https://www.r-inla.org>). Additionally, extends the GAM-like model class to more general nonlinear predictor expressions, and implements a log Gaussian Cox process likelihood for modeling univariate and spatial point processes based on ecological survey data. Model components are specified with general inputs and mapping methods to the latent variables, and the predictors are specified via general R expressions, with separate expressions for each observation likelihood model in multi-likelihood models. A prediction method based on fast Monte Carlo sampling allows posterior prediction of general expressions of the latent variables. Ecology-focused introduction in Bachl, Lindgren, Borchers, and Illian (2019) <doi:10.1111/2041-210X.13168>.
Maintained by Finn Lindgren. Last updated 1 days ago.
5.4 match 96 stars 12.61 score 832 scripts 6 dependentsncn-foreigners
singleRcapture:Single-Source Capture-Recapture Models
Implementation of single-source capture-recapture methods for population size estimation using zero-truncated, zero-one truncated and zero-truncated one-inflated Poisson, Geometric and Negative Binomial regression as well as Zelterman's and Chao's regression. Package includes point and interval estimators for the population size with variances estimated using analytical or bootstrap method. Details can be found in: van der Heijden et all. (2003) <doi:10.1191/1471082X03st057oa>, Böhning and van der Heijden (2019) <doi:10.1214/18-AOAS1232>, Böhning et al. (2020) Capture-Recapture Methods for the Social and Medical Sciences or Böhning and Friedl (2021) <doi:10.1007/s10260-021-00556-8>.
Maintained by Maciej Beręsewicz. Last updated 1 months ago.
11.0 match 11 stars 6.16 score 29 scriptsjohnnyzhz
WebPower:Basic and Advanced Statistical Power Analysis
This is a collection of tools for conducting both basic and advanced statistical power analysis including correlation, proportion, t-test, one-way ANOVA, two-way ANOVA, linear regression, logistic regression, Poisson regression, mediation analysis, longitudinal data analysis, structural equation modeling and multilevel modeling. It also serves as the engine for conducting power analysis online at <https://webpower.psychstat.org>.
Maintained by Zhiyong Zhang. Last updated 6 months ago.
12.2 match 8 stars 5.52 score 128 scriptslmaowisc
WR:Win Ratio Analysis of Composite Time-to-Event Outcomes
Implements various win ratio methodologies for composite endpoints of death and non-fatal events, including the (stratified) proportional win-fractions (PW) regression models (Mao and Wang, 2020 <doi:10.1111/biom.13382>), (stratified) two-sample tests with possibly recurrent nonfatal event, and sample size calculation for standard win ratio test (Mao et al., 2021 <doi:10.1111/biom.13501>).
Maintained by Lu Mao. Last updated 2 months ago.
10.8 match 6.11 score 43 scriptsthomasp85
ggraph:An Implementation of Grammar of Graphics for Graphs and Networks
The grammar of graphics as implemented in ggplot2 is a poor fit for graph and network visualizations due to its reliance on tabular data input. ggraph is an extension of the ggplot2 API tailored to graph visualizations and provides the same flexible approach to building up plots layer by layer.
Maintained by Thomas Lin Pedersen. Last updated 1 years ago.
ggplot-extensionggplot2graph-visualizationnetwork-visualizationvisualizationcpp
3.9 match 1.1k stars 16.96 score 9.2k scripts 111 dependentscbielow
PTXQC:Quality Report Generation for MaxQuant and mzTab Results
Generates Proteomics (PTX) quality control (QC) reports for shotgun LC-MS data analyzed with the MaxQuant software suite (from .txt files) or mzTab files (ideally from OpenMS 'QualityControl' tool). Reports are customizable (target thresholds, subsetting) and available in HTML or PDF format. Published in J. Proteome Res., Proteomics Quality Control: Quality Control Software for MaxQuant Results (2015) <doi:10.1021/acs.jproteome.5b00780>.
Maintained by Chris Bielow. Last updated 1 years ago.
drag-and-drophacktoberfestheatmapmatch-between-runsmaxquantmetricmztabopenmsproteomicsquality-controlquality-metricsreport
7.0 match 42 stars 9.35 score 105 scripts 1 dependentsandrewhooker
PopED:Population (and Individual) Optimal Experimental Design
Optimal experimental designs for both population and individual studies based on nonlinear mixed-effect models. Often this is based on a computation of the Fisher Information Matrix. This package was developed for pharmacometric problems, and examples and predefined models are available for these types of systems. The methods are described in Nyberg et al. (2012) <doi:10.1016/j.cmpb.2012.05.005>, and Foracchia et al. (2004) <doi:10.1016/S0169-2607(03)00073-7>.
Maintained by Andrew C. Hooker. Last updated 5 months ago.
nlmeoptimal-designpharmacodynamicspharmacokineticspharmacometricspkpdpopulationpopulation-model
6.8 match 33 stars 9.58 score 300 scripts 1 dependentsskembel
picante:Integrating Phylogenies and Ecology
Functions for phylocom integration, community analyses, null-models, traits and evolution. Implements numerous ecophylogenetic approaches including measures of community phylogenetic and trait diversity, phylogenetic signal, estimation of trait values for unobserved taxa, null models for community and phylogeny randomizations, and utility functions for data input/output and phylogeny plotting. A full description of package functionality and methods are provided by Kembel et al. (2010) <doi:10.1093/bioinformatics/btq166>.
Maintained by Steven W. Kembel. Last updated 2 years ago.
5.6 match 34 stars 11.42 score 1.1k scripts 16 dependentstomasfryda
h2o:R Interface for the 'H2O' Scalable Machine Learning Platform
R interface for 'H2O', the scalable open source machine learning platform that offers parallelized implementations of many supervised and unsupervised machine learning algorithms such as Generalized Linear Models (GLM), Gradient Boosting Machines (including XGBoost), Random Forests, Deep Neural Networks (Deep Learning), Stacked Ensembles, Naive Bayes, Generalized Additive Models (GAM), ANOVA GLM, Cox Proportional Hazards, K-Means, PCA, ModelSelection, Word2Vec, as well as a fully automatic machine learning algorithm (H2O AutoML).
Maintained by Tomas Fryda. Last updated 1 years ago.
7.8 match 3 stars 8.20 score 7.8k scripts 11 dependentsjepusto
scdhlm:Estimating Hierarchical Linear Models for Single-Case Designs
Provides a set of tools for estimating hierarchical linear models and effect sizes based on data from single-case designs. Functions are provided for calculating standardized mean difference effect sizes that are directly comparable to standardized mean differences estimated from between-subjects randomized experiments, as described in Hedges, Pustejovsky, and Shadish (2012) <DOI:10.1002/jrsm.1052>; Hedges, Pustejovsky, and Shadish (2013) <DOI:10.1002/jrsm.1086>; Pustejovsky, Hedges, and Shadish (2014) <DOI:10.3102/1076998614547577>; and Chen, Pustejovsky, Klingbeil, and Van Norman (2023) <DOI:10.1016/j.jsp.2023.02.002>. Includes an interactive web interface.
Maintained by James Pustejovsky. Last updated 1 years ago.
11.3 match 4 stars 5.62 score 52 scriptshyunseungkang
ivmodel:Statistical Inference and Sensitivity Analysis for Instrumental Variables Model
Carries out instrumental variable estimation of causal effects, including power analysis, sensitivity analysis, and diagnostics. See Kang, Jiang, Zhao, and Small (2021) <https://muse.jhu.edu/article/804372> for details.
Maintained by Hyunseung Kang. Last updated 2 years ago.
13.5 match 10 stars 4.69 score 97 scriptseasystats
bayestestR:Understand and Describe Bayesian Models and Posterior Distributions
Provides utilities to describe posterior distributions and Bayesian models. It includes point-estimates such as Maximum A Posteriori (MAP), measures of dispersion (Highest Density Interval - HDI; Kruschke, 2015 <doi:10.1016/C2012-0-00477-2>) and indices used for null-hypothesis testing (such as ROPE percentage, pd and Bayes factors). References: Makowski et al. (2021) <doi:10.21105/joss.01541>.
Maintained by Dominique Makowski. Last updated 18 hours ago.
bayes-factorsbayesfactorbayesianbayesian-frameworkcredible-intervaleasystatshacktoberfesthdimapposterior-distributionsrope
3.8 match 579 stars 16.84 score 2.2k scripts 82 dependentsindrajeetpatil
statsExpressions:Tidy Dataframes and Expressions with Statistical Details
Utilities for producing dataframes with rich details for the most common types of statistical approaches and tests: parametric, nonparametric, robust, and Bayesian t-test, one-way ANOVA, correlation analyses, contingency table analyses, and meta-analyses. The functions are pipe-friendly and provide a consistent syntax to work with tidy data. These dataframes additionally contain expressions with statistical details, and can be used in graphing packages. This package also forms the statistical processing backend for 'ggstatsplot'. References: Patil (2021) <doi:10.21105/joss.03236>.
Maintained by Indrajeet Patil. Last updated 22 days ago.
bayesian-inferencebayesian-statisticscontingency-tablecorrelationeffectsizemeta-analysisparametricrobustrobust-statisticsstatistical-detailsstatistical-teststidy
5.7 match 312 stars 10.97 score 146 scripts 2 dependentsmdrcny
PUMP:Power Under Multiplicity Project
Estimates power, minimum detectable effect size (MDES) and sample size requirements. The context is multilevel randomized experiments with multiple outcomes. The estimation takes into account the use of multiple testing procedures. Development of this package was supported by a grant from the Institute of Education Sciences (R305D170030). For a full package description, including a detailed technical appendix, see <doi:10.18637/jss.v108.i06>.
Maintained by Luke Miratrix. Last updated 22 days ago.
9.6 match 8 stars 6.52 score 13 scriptsjmanitz
samplingbook:Survey Sampling Procedures
Sampling procedures from the book 'Stichproben - Methoden und praktische Umsetzung mit R' by Goeran Kauermann and Helmut Kuechenhoff (2010).
Maintained by Juliane Manitz. Last updated 4 years ago.
sampling-methodssampling-procedures
13.1 match 2 stars 4.78 score 54 scriptsdgerlanc
bootES:Bootstrap Confidence Intervals on Effect Sizes
Calculate robust measures of effect sizes using the bootstrap.
Maintained by Daniel Gerlanc. Last updated 4 months ago.
bootstrapping-statisticseffect-sizesocial-sciencesstatistics
11.1 match 11 stars 5.63 score 62 scriptsjamesliley
OptHoldoutSize:Estimation of Optimal Size for a Holdout Set for Updating a Predictive Score
Predictive scores must be updated with care, because actions taken on the basis of existing risk scores causes bias in risk estimates from the updated score. A holdout set is a straightforward way to manage this problem: a proportion of the population is 'held-out' from computation of the previous risk score. This package provides tools to estimate a size for this holdout set and associated errors. Comprehensive vignettes are included. Please see: Haidar-Wehbe S, Emerson SR, Aslett LJM, Liley J (2022) <arXiv:2202.06374> for details of methods.
Maintained by James Liley. Last updated 3 years ago.
19.6 match 3.18 score 10 scriptsstatmanrobin
Stat2Data:Datasets for Stat2
Datasets for the textbook Stat2: Modeling with Regression and ANOVA (second edition). The package also includes data for the first edition, Stat2: Building Models for a World of Data and a few functions for plotting diagnostics.
Maintained by Robin Lock. Last updated 6 years ago.
12.6 match 5 stars 4.94 score 544 scriptssinnweja
haplo.stats:Statistical Analysis of Haplotypes with Traits and Covariates when Linkage Phase is Ambiguous
Routines for the analysis of indirectly measured haplotypes. The statistical methods assume that all subjects are unrelated and that haplotypes are ambiguous (due to unknown linkage phase of the genetic markers). The main functions are: haplo.em(), haplo.glm(), haplo.score(), and haplo.power(); all of which have detailed examples in the vignette.
Maintained by Jason P. Sinnwell. Last updated 6 months ago.
10.3 match 2 stars 5.98 score 96 scripts 12 dependentsdavidgohel
officer:Manipulation of Microsoft Word and PowerPoint Documents
Access and manipulate 'Microsoft Word', 'RTF' and 'Microsoft PowerPoint' documents from R. The package focuses on tabular and graphical reporting from R; it also provides two functions that let users get document content into data objects. A set of functions lets add and remove images, tables and paragraphs of text in new or existing documents. The package does not require any installation of Microsoft products to be able to write Microsoft files.
Maintained by David Gohel. Last updated 1 months ago.
ms-office-documentspowerpointword
3.9 match 630 stars 15.79 score 4.1k scripts 137 dependentscran
Sequential:Exact Sequential Analysis for Poisson and Binomial Data
Functions to calculate exact critical values, statistical power, expected time to signal, and required sample sizes for performing exact sequential analysis. All these calculations can be done for either Poisson or binomial data, for continuous or group sequential analyses, and for different types of rejection boundaries. In case of group sequential analyses, the group sizes do not have to be specified in advance and the alpha spending can be arbitrarily settled.
Maintained by Ivair Ramos Silva. Last updated 5 months ago.
18.6 match 2 stars 3.24 score 38 scripts 1 dependentsfbartos
RoBMA:Robust Bayesian Meta-Analyses
A framework for estimating ensembles of meta-analytic and meta-regression models (assuming either presence or absence of the effect, heterogeneity, publication bias, and moderators). The RoBMA framework uses Bayesian model-averaging to combine the competing meta-analytic models into a model ensemble, weights the posterior parameter distributions based on posterior model probabilities and uses Bayes factors to test for the presence or absence of the individual components (e.g., effect vs. no effect; Bartoš et al., 2022, <doi:10.1002/jrsm.1594>; Maier, Bartoš & Wagenmakers, 2022, <doi:10.1037/met0000405>). Users can define a wide range of prior distributions for + the effect size, heterogeneity, publication bias (including selection models and PET-PEESE), and moderator components. The package provides convenient functions for summary, visualizations, and fit diagnostics.
Maintained by František Bartoš. Last updated 1 months ago.
meta-analysismodel-averagingpublication-biasjagsopenblascpp
8.6 match 9 stars 6.97 score 53 scriptsgabferreira
phyloraster:Evolutionary Diversity Metrics for Raster Data
Phylogenetic Diversity (PD, Faith 1992), Evolutionary Distinctiveness (ED, Isaac et al. 2007), Phylogenetic Endemism (PE, Rosauer et al. 2009; Laffan et al. 2016), and Weighted Endemism (WE, Laffan et al. 2016) for presence-absence raster. Faith, D. P. (1992) <doi:10.1016/0006-3207(92)91201-3> Isaac, N. J. et al. (2007) <doi:10.1371/journal.pone.0000296> Laffan, S. W. et al. (2016) <doi:10.1111/2041-210X.12513> Rosauer, D. et al. (2009) <doi:10.1111/j.1365-294X.2009.04311.x>.
Maintained by Gabriela Alves-Ferreira. Last updated 18 days ago.
10.6 match 7 stars 5.66 score 33 scriptsncss-tech
aqp:Algorithms for Quantitative Pedology
The Algorithms for Quantitative Pedology (AQP) project was started in 2009 to organize a loosely-related set of concepts and source code on the topic of soil profile visualization, aggregation, and classification into this package (aqp). Over the past 8 years, the project has grown into a suite of related R packages that enhance and simplify the quantitative analysis of soil profile data. Central to the AQP project is a new vocabulary of specialized functions and data structures that can accommodate the inherent complexity of soil profile information; freeing the scientist to focus on ideas rather than boilerplate data processing tasks <doi:10.1016/j.cageo.2012.10.020>. These functions and data structures have been extensively tested and documented, applied to projects involving hundreds of thousands of soil profiles, and deeply integrated into widely used tools such as SoilWeb <https://casoilresource.lawr.ucdavis.edu/soilweb-apps>. Components of the AQP project (aqp, soilDB, sharpshootR, soilReports packages) serve an important role in routine data analysis within the USDA-NRCS Soil Science Division. The AQP suite of R packages offer a convenient platform for bridging the gap between pedometric theory and practice.
Maintained by Dylan Beaudette. Last updated 1 months ago.
digital-soil-mappingncss-technrcspedologypedometricssoilsoil-surveyusda
5.1 match 55 stars 11.90 score 1.2k scripts 2 dependentscran
ICC.Sample.Size:Calculation of Sample Size and Power for ICC
Provides functions to calculate the requisite sample size for studies where ICC is the primary outcome. Can also be used for calculation of power. In both cases it allows the user to test the impact of changing input variables by calculating the outcome for several different values of input variables. Based off the work of Zou. Zou, G. Y. (2012). Sample size formulas for estimating intraclass correlation coefficients with precision and assurance. Statistics in medicine, 31(29), 3972-3981.
Maintained by Alasdair Rathbone. Last updated 10 years ago.
40.6 match 1.48 score 1 dependentspolkas
pacs:Supplementary Tools for R Packages Developers
Supplementary utils for CRAN maintainers and R packages developers. Validating the library, packages and lock files. Exploring a complexity of a specific package like evaluating its size in bytes with all dependencies. The shiny app complexity could be explored too. Assessing the life duration of a specific package version. Checking a CRAN package check page status for any errors and warnings. Retrieving a DESCRIPTION or NAMESPACE file for any package version. Comparing DESCRIPTION or NAMESPACE files between different package versions. Getting a list of all releases for a specific package. The Bioconductor is partly supported.
Maintained by Maciej Nasinski. Last updated 6 months ago.
bioconductordependencieslibrarylifedurationrenvshinytoolsutils
10.5 match 25 stars 5.70 score 8 scriptsmalcolmbarrett
precisely:Estimate Sample Size Based on Precision Rather than Power
Estimate sample size based on precision rather than power. 'precisely' is a study planning tool to calculate sample size based on precision. Power calculations are focused on whether or not an estimate will be statistically significant; calculations of precision are based on the same principles as power calculation but turn the focus to the width of the confidence interval. 'precisely' is based on the work of 'Rothman and Greenland' (2018).
Maintained by Malcolm Barrett. Last updated 3 years ago.
10.1 match 94 stars 5.93 score 18 scriptskharchenkolab
numbat:Haplotype-Aware CNV Analysis from scRNA-Seq
A computational method that infers copy number variations (CNVs) in cancer scRNA-seq data and reconstructs the tumor phylogeny. 'numbat' integrates signals from gene expression, allelic ratio, and population haplotype structures to accurately infer allele-specific CNVs in single cells and reconstruct their lineage relationship. 'numbat' can be used to: 1. detect allele-specific copy number variations from single-cells; 2. differentiate tumor versus normal cells in the tumor microenvironment; 3. infer the clonal architecture and evolutionary history of profiled tumors. 'numbat' does not require tumor/normal-paired DNA or genotype data, but operates solely on the donor scRNA-data data (for example, 10x Cell Ranger output). Additional examples and documentations are available at <https://kharchenkolab.github.io/numbat/>. For details on the method please see Gao et al. Nature Biotechnology (2022) <doi:10.1038/s41587-022-01468-y>.
Maintained by Teng Gao. Last updated 18 days ago.
cancer-genomicscnv-detectionlineage-tracingphylogenysingle-cellsingle-cell-analysissingle-cell-rna-seqspatial-transcriptomicscpp
8.0 match 179 stars 7.41 score 120 scriptstidymodels
dials:Tools for Creating Tuning Parameter Values
Many models contain tuning parameters (i.e. parameters that cannot be directly estimated from the data). These tools can be used to define objects for creating, simulating, or validating values for such parameters.
Maintained by Hannah Frick. Last updated 1 months ago.
4.1 match 114 stars 14.31 score 426 scripts 52 dependentsepiverse-trace
epidemics:Composable Epidemic Scenario Modelling
A library of compartmental epidemic models taken from the published literature, and classes to represent affected populations, public health response measures including non-pharmaceutical interventions on social contacts, non-pharmaceutical and pharmaceutical interventions that affect disease transmissibility, vaccination regimes, and disease seasonality, which can be combined to compose epidemic scenario models.
Maintained by Rosalind Eggo. Last updated 9 months ago.
decision-supportepidemic-modellingepidemic-simulationsepidemiologyepiverseinfectious-disease-dynamicsmodel-librarynon-pharmaceutical-interventionsrcpprcppeigenscenario-analysisvaccinationcpp
7.9 match 9 stars 7.48 score 59 scriptstraitecoevo
hmde:Hierarchical Methods for Differential Equations
Wrapper for Stan that offers a number of in-built models to implement a hierarchical Bayesian longitudinal model for repeat observation data. Model choice selects the differential equation that is fit to the observations. Single and multi-individual models are available.
Maintained by Tess OBrien. Last updated 1 months ago.
bayesian-inverse-problemsbayesian-methodsdifferential-equationshierarchical-modelsrstanstancpp
10.6 match 3 stars 5.53 score 10 scriptsstatimagcoll
RESI:Robust Effect Size Index (RESI) Estimation
Summarize model output using a robust effect size index. The index is introduced in Vandekar, Tao, & Blume (2020) <doi:10.1007/s11336-020-09698-2>.
Maintained by Megan Jones. Last updated 15 days ago.
13.5 match 4.30 score 20 scriptsr-forge
coin:Conditional Inference Procedures in a Permutation Test Framework
Conditional inference procedures for the general independence problem including two-sample, K-sample (non-parametric ANOVA), correlation, censored, ordered and multivariate problems described in <doi:10.18637/jss.v028.i08>.
Maintained by Torsten Hothorn. Last updated 9 months ago.
4.9 match 11.68 score 1.6k scripts 74 dependentsshinra-dev
memuse:Memory Estimation Utilities
How much ram do you need to store a 100,000 by 100,000 matrix? How much ram is your current R session using? How much ram do you even have? Learn the scintillating answer to these and many more such questions with the 'memuse' package.
Maintained by Drew Schmidt. Last updated 2 years ago.
6.5 match 46 stars 8.84 score 142 scripts 34 dependentsqile0317
APackOfTheClones:Visualization of Clonal Expansion for Single Cell Immune Profiles
Visualize clonal expansion via circle-packing. 'APackOfTheClones' extends 'scRepertoire' to produce a publication-ready visualization of clonal expansion at a single cell resolution, by representing expanded clones as differently sized circles. The method was originally implemented by Murray Christian and Ben Murrell in the following immunology study: Ma et al. (2021) <doi:10.1126/sciimmunol.abg6356>.
Maintained by Qile Yang. Last updated 4 months ago.
clonal-analysisimmune-repertoireimmune-systemscrna-seqscrnaseqseuratsingle-cellsingle-cell-genomicscpp
8.8 match 15 stars 6.45 score 15 scriptslbbe-software
fitdistrplus:Help to Fit of a Parametric Distribution to Non-Censored or Censored Data
Extends the fitdistr() function (of the MASS package) with several functions to help the fit of a parametric distribution to non-censored or censored data. Censored data may contain left censored, right censored and interval censored values, with several lower and upper bounds. In addition to maximum likelihood estimation (MLE), the package provides moment matching (MME), quantile matching (QME), maximum goodness-of-fit estimation (MGE) and maximum spacing estimation (MSE) methods (available only for non-censored data). Weighted versions of MLE, MME, QME and MSE are available. See e.g. Casella & Berger (2002), Statistical inference, Pacific Grove, for a general introduction to parametric estimation.
Maintained by Aurélie Siberchicot. Last updated 14 days ago.
3.5 match 54 stars 16.15 score 4.5k scripts 153 dependentshojsgaard
doBy:Groupwise Statistics, LSmeans, Linear Estimates, Utilities
Utility package containing: 1) Facilities for working with grouped data: 'do' something to data stratified 'by' some variables. 2) LSmeans (least-squares means), general linear estimates. 3) Restrict functions to a smaller domain. 4) Miscellaneous other utilities.
Maintained by Søren Højsgaard. Last updated 6 days ago.
3.8 match 1 stars 14.94 score 3.2k scripts 939 dependentsropensci
tracerer:Tracer from R
'BEAST2' (<https://www.beast2.org>) is a widely used Bayesian phylogenetic tool, that uses DNA/RNA/protein data and many model priors to create a posterior of jointly estimated phylogenies and parameters. 'Tracer' (<https://github.com/beast-dev/tracer/>) is a GUI tool to parse and analyze the files generated by 'BEAST2'. This package provides a way to parse and analyze 'BEAST2' input files without active user input, but using R function calls instead.
Maintained by Richèl J.C. Bilderbeek. Last updated 1 years ago.
8.6 match 8 stars 6.49 score 86 scripts 3 dependentsludvigolsen
groupdata2:Creating Groups from Data
Methods for dividing data into groups. Create balanced partitions and cross-validation folds. Perform time series windowing and general grouping and splitting of data. Balance existing groups with up- and downsampling or collapse them to fewer groups.
Maintained by Ludvig Renbo Olsen. Last updated 3 months ago.
balancecross-validationdatadata-framefoldgroup-factorgroupsparticipantspartitionsplitstaircase
6.2 match 27 stars 9.04 score 338 scripts 7 dependentsnetfacs
NetFACS:Network Applications to Facial Communication Data
Functions to analyze and visualize communication data, based on network theory and resampling methods. Farine, D. R. (2017) <doi:10.1111/2041-210X.12772>; Carsey, T., & Harden, J. (2014) <doi:10.4135/9781483319605>. Primarily targeted at datasets of facial expressions coded with the Facial Action Coding System. Ekman, P., Friesen, W. V., & Hager, J. C. (2002). "Facial action coding system - investigator's guide" <https://www.paulekman.com/facial-action-coding-system/>.
Maintained by Alan V. Rincon. Last updated 11 months ago.
11.0 match 8 stars 5.08 score 5 scriptsbioc
ALDEx2:Analysis Of Differential Abundance Taking Sample and Scale Variation Into Account
A differential abundance analysis for the comparison of two or more conditions. Useful for analyzing data from standard RNA-seq or meta-RNA-seq assays as well as selected and unselected values from in-vitro sequence selections. Uses a Dirichlet-multinomial model to infer abundance from counts, optimized for three or more experimental replicates. The method infers biological and sampling variation to calculate the expected false discovery rate, given the variation, based on a Wilcoxon Rank Sum test and Welch's t-test (via aldex.ttest), a Kruskal-Wallis test (via aldex.kw), a generalized linear model (via aldex.glm), or a correlation test (via aldex.corr). All tests report predicted p-values and posterior Benjamini-Hochberg corrected p-values. ALDEx2 also calculates expected standardized effect sizes for paired or unpaired study designs. ALDEx2 can now be used to estimate the effect of scale on the results and report on the scale-dependent robustness of results.
Maintained by Greg Gloor. Last updated 5 months ago.
differentialexpressionrnaseqtranscriptomicsgeneexpressiondnaseqchipseqbayesiansequencingsoftwaremicrobiomemetagenomicsimmunooncologyscale simulationposterior p-value
5.2 match 28 stars 10.70 score 424 scripts 3 dependentsbioc
bayNorm:Single-cell RNA sequencing data normalization
bayNorm is used for normalizing single-cell RNA-seq data.
Maintained by Wenhao Tang. Last updated 5 months ago.
immunooncologynormalizationrnaseqsinglecellsequencingscrnaseqcppopenmp
8.4 match 9 stars 6.59 score 36 scriptsmarcusrowcliffe
sbd:Size Biased Distributions
Fitting and plotting parametric or non-parametric size-biased non-negative distributions, with optional covariates if parametric. Rowcliffe, M. et al. (2016) <doi:10.1002/rse2.17>.
Maintained by Marcus Rowcliffe. Last updated 9 months ago.
16.8 match 3.30 scorehemingnm
SESraster:Raster Randomization for Null Hypothesis Testing
Randomization of presence/absence species distribution raster data with or without including spatial structure for calculating standardized effect sizes and testing null hypothesis. The randomization algorithms are based on classical algorithms for matrices (Gotelli 2000, <doi:10.2307/177478>) implemented for raster data.
Maintained by Neander Marcel Heming. Last updated 5 months ago.
null-modelsrandomizationrasterspatialspatial-analysisspecies-distribution-modelling
8.3 match 7 stars 6.61 score 32 scripts 2 dependentsfsavje
scclust:Size-Constrained Clustering
Provides wrappers for 'scclust', a C library for computationally efficient size-constrained clustering with near-optimal performance. See <https://github.com/fsavje/scclust> for more information.
Maintained by Fredrik Savje. Last updated 1 years ago.
9.6 match 31 stars 5.64 score 41 scripts 2 dependentsthlytras
miniMeta:Web Application to Run Meta-Analyses
Shiny web application to run meta-analyses. Essentially a graphical front-end to package 'meta' for R. Can be useful as an educational tool, and for quickly analyzing and sharing meta-analyses. Provides output to quickly fill in GRADE (Grading of Recommendations, Assessment, Development and Evaluations) Summary-of-Findings tables. Importantly, it allows further processing of the results inside R, in case more specific analyses are needed.
Maintained by Theodore Lytras. Last updated 9 months ago.
meta-analysesmeta-analysisobservational-studiesrandomized-controlled-trialssample-size-calculationshiny
11.5 match 5 stars 4.70 score 3 scriptscran
mgcv:Mixed GAM Computation Vehicle with Automatic Smoothness Estimation
Generalized additive (mixed) models, some of their extensions and other generalized ridge regression with multiple smoothing parameter estimation by (Restricted) Marginal Likelihood, Generalized Cross Validation and similar, or using iterated nested Laplace approximation for fully Bayesian inference. See Wood (2017) <doi:10.1201/9781315370279> for an overview. Includes a gam() function, a wide variety of smoothers, 'JAGS' support and distributions beyond the exponential family.
Maintained by Simon Wood. Last updated 1 years ago.
4.3 match 32 stars 12.71 score 17k scripts 7.8k dependentsms609
TreeDist:Calculate and Map Distances Between Phylogenetic Trees
Implements measures of tree similarity, including information-based generalized Robinson-Foulds distances (Phylogenetic Information Distance, Clustering Information Distance, Matching Split Information Distance; Smith 2020) <doi:10.1093/bioinformatics/btaa614>; Jaccard-Robinson-Foulds distances (Bocker et al. 2013) <doi:10.1007/978-3-642-40453-5_13>, including the Nye et al. (2006) metric <doi:10.1093/bioinformatics/bti720>; the Matching Split Distance (Bogdanowicz & Giaro 2012) <doi:10.1109/TCBB.2011.48>; Maximum Agreement Subtree distances; the Kendall-Colijn (2016) distance <doi:10.1093/molbev/msw124>, and the Nearest Neighbour Interchange (NNI) distance, approximated per Li et al. (1996) <doi:10.1007/3-540-61332-3_168>. Includes tools for visualizing mappings of tree space (Smith 2022) <doi:10.1093/sysbio/syab100>, for identifying islands of trees (Silva and Wilkinson 2021) <doi:10.1093/sysbio/syab015>, for calculating the median of sets of trees, and for computing the information content of trees and splits.
Maintained by Martin R. Smith. Last updated 1 months ago.
phylogeneticstree-distancephylogenetic-treestree-distancestreescpp
5.2 match 32 stars 10.32 score 97 scripts 5 dependentssfcheung
manymome:Mediation, Moderation and Moderated-Mediation After Model Fitting
Computes indirect effects, conditional effects, and conditional indirect effects in a structural equation model or path model after model fitting, with no need to define any user parameters or label any paths in the model syntax, using the approach presented in Cheung and Cheung (2024) <doi:10.3758/s13428-023-02224-z>. Can also form bootstrap confidence intervals by doing bootstrapping only once and reusing the bootstrap estimates in all subsequent computations. Supports bootstrap confidence intervals for standardized (partially or completely) indirect effects, conditional effects, and conditional indirect effects as described in Cheung (2009) <doi:10.3758/BRM.41.2.425> and Cheung, Cheung, Lau, Hui, and Vong (2022) <doi:10.1037/hea0001188>. Model fitting can be done by structural equation modeling using lavaan() or regression using lm().
Maintained by Shu Fai Cheung. Last updated 24 days ago.
bootstrappingconfidence-intervallavaanmanymomemediationmoderated-mediationmoderationregressionsemstandardized-effect-sizestructural-equation-modeling
6.7 match 1 stars 8.06 score 172 scripts 4 dependentsmikldk
malan:MAle Lineage ANalysis
MAle Lineage ANalysis by simulating genealogies backwards and imposing short tandem repeats (STR) mutations forwards. Intended for forensic Y chromosomal STR (Y-STR) haplotype analyses. Numerous analyses are possible, e.g. number of matches and meiotic distance to matches. Refer to papers mentioned in citation("malan") (DOI's: <doi:10.1371/journal.pgen.1007028>, <doi:10.21105/joss.00684> and <doi:10.1016/j.fsigen.2018.10.004>).
Maintained by Mikkel Meyer Andersen. Last updated 1 years ago.
12.0 match 4.48 score 6 scriptsakkyro
PupilPre:Preprocessing Pupil Size Data
Pupillometric data collected using SR Research Eyelink eye trackers requires significant preprocessing. This package contains functions for preparing pupil dilation data for visualization and statistical analysis. Specifically, it provides a pipeline of functions which aid in data validation, the removal of blinks/artifacts, downsampling, and baselining, among others. Additionally, plotting functions for creating grand average and conditional average plots are provided. See the vignette for samples of the functionality. The package is designed for handling data collected with SR Research Eyelink eye trackers using Sample Reports created in SR Research Data Viewer.
Maintained by Aki-Juhani Kyröläinen. Last updated 5 years ago.
19.0 match 2.81 score 13 scriptsegenn
rtemis:Machine Learning and Visualization
Advanced Machine Learning and Visualization. Unsupervised Learning (Clustering, Decomposition), Supervised Learning (Classification, Regression), Cross-Decomposition, Bagging, Boosting, Meta-models. Static and interactive graphics.
Maintained by E.D. Gennatas. Last updated 1 months ago.
data-sciencedata-visualizationmachine-learningmachine-learning-libraryvisualization
7.6 match 145 stars 7.09 score 50 scripts 2 dependentsbaptiste
egg:Extensions for 'ggplot2': Custom Geom, Custom Themes, Plot Alignment, Labelled Panels, Symmetric Scales, and Fixed Panel Size
Miscellaneous functions to help customise 'ggplot2' objects. High-level functions are provided to post-process 'ggplot2' layouts and allow alignment between plot panels, as well as setting panel sizes to fixed values. Other functions include a custom 'geom', and helper functions to enforce symmetric scales or add tags to facetted plots.
Maintained by Baptiste Auguie. Last updated 4 years ago.
4.5 match 13 stars 11.84 score 2.4k scripts 67 dependentssbgraves237
Ecdat:Data Sets for Econometrics
Data sets for econometrics, including political science.
Maintained by Spencer Graves. Last updated 4 months ago.
7.3 match 2 stars 7.25 score 740 scripts 3 dependentssacema
inctools:Incidence Estimation Tools
Tools for estimating incidence from biomarker data in cross- sectional surveys, and for calibrating tests for recent infection. Implements and extends the method of Kassanjee et al. (2012) <doi:10.1097/EDE.0b013e3182576c07>.
Maintained by Eduard Grebe. Last updated 4 years ago.
biomarkersbiostatisticsepidemiologyhivincidenceincidence-estimationincidence-inferenceinfectious-diseasesstatistics
8.2 match 6 stars 6.51 score 27 scriptsddalthorp
GenEst:Generalized Mortality Estimator
Command-line and 'shiny' GUI implementation of the GenEst models for estimating bird and bat mortality at wind and solar power facilities, following Dalthorp, et al. (2018) <doi:10.3133/tm7A2>.
Maintained by Daniel Dalthorp. Last updated 2 years ago.
6.7 match 7 stars 7.81 score 55 scripts 2 dependentssamhforbes
PupillometryR:A Unified Pipeline for Pupillometry Data
Provides a unified pipeline to clean, prepare, plot, and run basic analyses on pupillometry experiments.
Maintained by Samuel Forbes. Last updated 1 years ago.
6.9 match 44 stars 7.58 score 288 scripts 1 dependentsaguerozz
SPCompute:Compute Power or Sample Size for GWAS with Covariate Effect
Fast computation of the required sample size or the achieved power, for GWAS studies with different types of covariate effects and different types of covariate-gene dependency structure. For the detailed description of the methodology, see Zhang (2022) "Power and Sample Size Computation for Genetic Association Studies of Binary Traits: Accounting for Covariate Effects" <arXiv:2203.15641>.
Maintained by Ziang Zhang. Last updated 2 years ago.
13.6 match 3.81 score 13 scriptscdueben
cppcontainers:'C++' Standard Template Library Containers
Use 'C++' Standard Template Library containers interactively in R. Includes sets, unordered sets, multisets, unordered multisets, maps, unordered maps, multimaps, unordered multimaps, stacks, queues, priority queues, vectors, deques, forward lists, and lists.
Maintained by Christian Düben. Last updated 2 months ago.
11.1 match 4.70 score 1 scriptseogrady21
vprr:Processing and Visualization of Video Plankton Recorder Data
An oceanographic data processing package for analyzing and visualizing Video Plankton Recorder data. This package was developed at 'Bedford Institute of Oceanography'. Functions are designed to process automated image classification output and create organized and easily portable data products.
Maintained by Emily OGrady. Last updated 1 months ago.
9.2 match 2 stars 5.61 score 17 scriptsrvalavi
blockCV:Spatial and Environmental Blocking for K-Fold and LOO Cross-Validation
Creating spatially or environmentally separated folds for cross-validation to provide a robust error estimation in spatially structured environments; Investigating and visualising the effective range of spatial autocorrelation in continuous raster covariates and point samples to find an initial realistic distance band to separate training and testing datasets spatially described in Valavi, R. et al. (2019) <doi:10.1111/2041-210X.13107>.
Maintained by Roozbeh Valavi. Last updated 5 months ago.
cross-validationspatialspatial-cross-validationspatial-modellingspecies-distribution-modellingcpp
4.9 match 113 stars 10.49 score 302 scripts 3 dependentsneonscience
neonUtilities:Utilities for Working with NEON Data
NEON data packages can be accessed through the NEON Data Portal <https://www.neonscience.org> or through the NEON Data API (see <https://data.neonscience.org/data-api> for documentation). Data delivered from the Data Portal are provided as monthly zip files packaged within a parent zip file, while individual files can be accessed from the API. This package provides tools that aid in discovering, downloading, and reformatting data prior to use in analyses. This includes downloading data via the API, merging data tables by type, and converting formats. For more information, see the readme file at <https://github.com/NEONScience/NEON-utilities>.
Maintained by Claire Lunch. Last updated 1 months ago.
4.8 match 57 stars 10.66 score 944 scripts 15 dependentsthijsjanzen
GUILDS:Implementation of Sampling Formulas for the Unified Neutral Model of Biodiversity and Biogeography, with or without Guild Structure
A collection of sampling formulas for the unified neutral model of biogeography and biodiversity. Alongside the sampling formulas, it includes methods to perform maximum likelihood optimization of the sampling formulas, methods to generate data given the neutral model, and methods to estimate the expected species abundance distribution. Sampling formulas included in the GUILDS package are the Etienne Sampling Formula (Etienne 2005), the guild sampling formula, where guilds are assumed to differ in dispersal ability (Janzen et al. 2015), and the guilds sampling formula conditioned on guild size (Janzen et al. 2015).
Maintained by Thijs Janzen. Last updated 5 days ago.
9.4 match 2 stars 5.43 score 18 scripts 5 dependentsphilchalmers
mirt:Multidimensional Item Response Theory
Analysis of discrete response data using unidimensional and multidimensional item analysis models under the Item Response Theory paradigm (Chalmers (2012) <doi:10.18637/jss.v048.i06>). Exploratory and confirmatory item factor analysis models are estimated with quadrature (EM) or stochastic (MHRM) methods. Confirmatory bi-factor and two-tier models are available for modeling item testlets using dimension reduction EM algorithms, while multiple group analyses and mixed effects designs are included for detecting differential item, bundle, and test functioning, and for modeling item and person covariates. Finally, latent class models such as the DINA, DINO, multidimensional latent class, mixture IRT models, and zero-inflated response models are supported, as well as a wide family of probabilistic unfolding models.
Maintained by Phil Chalmers. Last updated 13 days ago.
3.4 match 210 stars 14.98 score 2.5k scripts 40 dependentsplangfelder
WGCNA:Weighted Correlation Network Analysis
Functions necessary to perform Weighted Correlation Network Analysis on high-dimensional data as originally described in Horvath and Zhang (2005) <doi:10.2202/1544-6115.1128> and Langfelder and Horvath (2008) <doi:10.1186/1471-2105-9-559>. Includes functions for rudimentary data cleaning, construction of correlation networks, module identification, summarization, and relating of variables and modules to sample traits. Also includes a number of utility functions for data manipulation and visualization.
Maintained by Peter Langfelder. Last updated 6 months ago.
5.3 match 54 stars 9.65 score 5.3k scripts 32 dependentsarsilva87
soilphysics:Soil Physical Analysis
Basic and model-based soil physical analyses.
Maintained by Anderson Rodrigo da Silva. Last updated 3 years ago.
10.4 match 11 stars 4.83 score 12 scriptswinvector
sigr:Succinct and Correct Statistical Summaries for Reports
Succinctly and correctly format statistical summaries of various models and tests (F-test, Chi-Sq-test, Fisher-test, T-test, and rank-significance). This package also includes empirical tests, such as Monte Carlo and bootstrap distribution estimates.
Maintained by John Mount. Last updated 2 years ago.
7.0 match 28 stars 7.18 score 97 scripts 1 dependentsbioc
singleCellTK:Comprehensive and Interactive Analysis of Single Cell RNA-Seq Data
The Single Cell Toolkit (SCTK) in the singleCellTK package provides an interface to popular tools for importing, quality control, analysis, and visualization of single cell RNA-seq data. SCTK allows users to seamlessly integrate tools from various packages at different stages of the analysis workflow. A general "a la carte" workflow gives users the ability access to multiple methods for data importing, calculation of general QC metrics, doublet detection, ambient RNA estimation and removal, filtering, normalization, batch correction or integration, dimensionality reduction, 2-D embedding, clustering, marker detection, differential expression, cell type labeling, pathway analysis, and data exporting. Curated workflows can be used to run Seurat and Celda. Streamlined quality control can be performed on the command line using the SCTK-QC pipeline. Users can analyze their data using commands in the R console or by using an interactive Shiny Graphical User Interface (GUI). Specific analyses or entire workflows can be summarized and shared with comprehensive HTML reports generated by Rmarkdown. Additional documentation and vignettes can be found at camplab.net/sctk.
Maintained by Joshua David Campbell. Last updated 26 days ago.
singlecellgeneexpressiondifferentialexpressionalignmentclusteringimmunooncologybatcheffectnormalizationqualitycontroldataimportgui
4.9 match 181 stars 10.16 score 252 scriptsmyaseen208
PakPC2023:Pakistan Population Census 2023
Provides data sets and functions for exploration of Pakistan Population Census 2023 (<https://www.pbs.gov.pk/>).
Maintained by Muhammad Yaseen. Last updated 5 months ago.
12.0 match 1 stars 4.18 score 2 scripts 1 dependentsbiodiverse
unmarked:Models for Data from Unmarked Animals
Fits hierarchical models of animal abundance and occurrence to data collected using survey methods such as point counts, site occupancy sampling, distance sampling, removal sampling, and double observer sampling. Parameters governing the state and observation processes can be modeled as functions of covariates. References: Kellner et al. (2023) <doi:10.1111/2041-210X.14123>, Fiske and Chandler (2011) <doi:10.18637/jss.v043.i10>.
Maintained by Ken Kellner. Last updated 3 days ago.
3.8 match 4 stars 13.03 score 652 scripts 12 dependentsedzer
intervals:Tools for Working with Points and Intervals
Tools for working with and comparing sets of points and intervals.
Maintained by Edzer Pebesma. Last updated 7 months ago.
5.3 match 11 stars 9.40 score 122 scripts 90 dependents