Showing 65 of total 65 results (show query)
wviechtb
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 5 days ago.
meta-analysismixed-effectsmultilevel-modelsmultivariate
250 stars 16.32 score 4.9k scripts 92 dependents
guido-s
meta:General Package for Meta-Analysis
User-friendly general package providing standard methods for meta-analysis and supporting Schwarzer, Carpenter, and Rücker <DOI:10.1007/978-3-319-21416-0>, "Meta-Analysis with R" (2015): - common effect and random effects meta-analysis; - several plots (forest, funnel, Galbraith / radial, L'Abbe, Baujat, bubble); - three-level meta-analysis model; - generalised linear mixed model; - logistic regression with penalised likelihood for rare events; - Hartung-Knapp method for random effects model; - Kenward-Roger method for random effects model; - prediction interval; - statistical tests for funnel plot asymmetry; - trim-and-fill method to evaluate bias in meta-analysis; - meta-regression; - cumulative meta-analysis and leave-one-out meta-analysis; - import data from 'RevMan 5'; - produce forest plot summarising several (subgroup) meta-analyses.
Maintained by Guido Schwarzer. Last updated 5 days ago.
89 stars 14.95 score 2.3k scripts 30 dependents
pecanproject
PEcAn.DB:PEcAn Functions Used for Ecological Forecasts and Reanalysis
The Predictive Ecosystem Carbon Analyzer (PEcAn) is a scientific workflow management tool that is designed to simplify the management of model parameterization, execution, and analysis. The goal of PECAn is to streamline the interaction between data and models, and to improve the efficacy of scientific investigation.
Maintained by David LeBauer. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplants
216 stars 11.90 score 127 scripts 27 dependentsguido-s
netmeta:Network Meta-Analysis using Frequentist Methods
A comprehensive set of functions providing frequentist methods for network meta-analysis (Balduzzi et al., 2023) <doi:10.18637/jss.v106.i02> and supporting Schwarzer et al. (2015) <doi:10.1007/978-3-319-21416-0>, Chapter 8 "Network Meta-Analysis": - frequentist network meta-analysis following Rücker (2012) <doi:10.1002/jrsm.1058>; - additive network meta-analysis for combinations of treatments (Rücker et al., 2020) <doi:10.1002/bimj.201800167>; - network meta-analysis of binary data using the Mantel-Haenszel or non-central hypergeometric distribution method (Efthimiou et al., 2019) <doi:10.1002/sim.8158>, or penalised logistic regression (Evrenoglou et al., 2022) <doi:10.1002/sim.9562>; - rankograms and ranking of treatments by the Surface under the cumulative ranking curve (SUCRA) (Salanti et al., 2013) <doi:10.1016/j.jclinepi.2010.03.016>; - ranking of treatments using P-scores (frequentist analogue of SUCRAs without resampling) according to Rücker & Schwarzer (2015) <doi:10.1186/s12874-015-0060-8>; - split direct and indirect evidence to check consistency (Dias et al., 2010) <doi:10.1002/sim.3767>, (Efthimiou et al., 2019) <doi:10.1002/sim.8158>; - league table with network meta-analysis results; - 'comparison-adjusted' funnel plot (Chaimani & Salanti, 2012) <doi:10.1002/jrsm.57>; - net heat plot and design-based decomposition of Cochran's Q according to Krahn et al. (2013) <doi:10.1186/1471-2288-13-35>; - measures characterizing the flow of evidence between two treatments by König et al. (2013) <doi:10.1002/sim.6001>; - automated drawing of network graphs described in Rücker & Schwarzer (2016) <doi:10.1002/jrsm.1143>; - partial order of treatment rankings ('poset') and Hasse diagram for 'poset' (Carlsen & Bruggemann, 2014) <doi:10.1002/cem.2569>; (Rücker & Schwarzer, 2017) <doi:10.1002/jrsm.1270>; - contribution matrix as described in Papakonstantinou et al. (2018) <doi:10.12688/f1000research.14770.3> and Davies et al. (2022) <doi:10.1002/sim.9346>; - subgroup network meta-analysis.
Maintained by Guido Schwarzer. Last updated 12 days ago.
meta-analysisnetwork-meta-analysisrstudio
33 stars 11.84 score 199 scripts 10 dependentspecanproject
PEcAn.data.atmosphere:PEcAn Functions Used for Managing Climate Driver Data
The Predictive Ecosystem Carbon Analyzer (PEcAn) is a scientific workflow management tool that is designed to simplify the management of model parameterization, execution, and analysis. The PECAn.data.atmosphere package converts climate driver data into a standard format for models integrated into PEcAn. As a standalone package, it provides an interface to access diverse climate data sets.
Maintained by David LeBauer. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplants
216 stars 11.62 score 64 scripts 14 dependents
ropensci
biomartr:Genomic Data Retrieval
Perform large scale genomic data retrieval and functional annotation retrieval. This package aims to provide users with a standardized way to automate genome, proteome, 'RNA', coding sequence ('CDS'), 'GFF', and metagenome retrieval from 'NCBI RefSeq', 'NCBI Genbank', 'ENSEMBL', and 'UniProt' databases. Furthermore, an interface to the 'BioMart' database (Smedley et al. (2009) <doi:10.1186/1471-2164-10-22>) allows users to retrieve functional annotation for genomic loci. In addition, users can download entire databases such as 'NCBI RefSeq' (Pruitt et al. (2007) <doi:10.1093/nar/gkl842>), 'NCBI nr', 'NCBI nt', 'NCBI Genbank' (Benson et al. (2013) <doi:10.1093/nar/gks1195>), etc. with only one command.
Maintained by Hajk-Georg Drost. Last updated 2 months ago.
biomartgenomic-data-retrievalannotation-retrievaldatabase-retrievalncbiensemblbiological-data-retrievalensembl-serversgenomegenome-annotationgenome-retrievalgenomicsmeta-analysismetagenomicsncbi-genbankpeer-reviewedproteomesequenced-genomes
218 stars 11.35 score 129 scripts 3 dependentspecanproject
PEcAn.visualization:PEcAn visualization functions
The Predictive Ecosystem Carbon Analyzer (PEcAn) is a scientific workflow management tool that is designed to simplify the management of model parameterization, execution, and analysis. The goal of PECAn is to streamline the interaction between data and models, and to improve the efficacy of scientific investigation. This module is used to create more complex visualizations from the data generated by PEcAn code, specifically the models.
Maintained by David LeBauer. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplants
216 stars 10.97 score 74 scripts 11 dependentspecanproject
PEcAn.utils:PEcAn Functions Used for Ecological Forecasts and Reanalysis
The Predictive Ecosystem Carbon Analyzer (PEcAn) is a scientific workflow management tool that is designed to simplify the management of model parameterization, execution, and analysis. The goal of PEcAn is to streamline the interaction between data and models, and to improve the efficacy of scientific investigation.
Maintained by Rob Kooper. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplants
216 stars 10.94 score 218 scripts 35 dependents
indrajeetpatil
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 1 months ago.
bayesian-inferencebayesian-statisticscontingency-tablecorrelationeffectsizemeta-analysisparametricrobustrobust-statisticsstatistical-detailsstatistical-teststidy
312 stars 10.92 score 146 scripts 2 dependentspecanproject
PEcAn.benchmark:PEcAn Functions Used for Benchmarking
The Predictive Ecosystem Carbon Analyzer (PEcAn) is a scientific workflow management tool that is designed to simplify the management of model parameterization, execution, and analysis. The goal of PEcAn is to streamline the interaction between data and models, and to improve the efficacy of scientific investigation. The PEcAn.benchmark package provides utilities for comparing models and data, including a suite of statistical metrics and plots.
Maintained by Mike Dietze. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplants
216 stars 10.72 score 416 scripts 11 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 1 days ago.
30 stars 10.61 score 65 scripts 93 dependentspecanproject
PEcAn.settings:PEcAn Settings package
Contains functions to read PEcAn settings files.
Maintained by David LeBauer. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplants
216 stars 10.02 score 54 scripts 17 dependentspecanproject
PEcAn.assim.batch:PEcAn Functions Used for Ecological Forecasts and Reanalysis
The Predictive Ecosystem Carbon Analyzer (PEcAn) is a scientific workflow management tool that is designed to simplify the management of model parameterization, execution, and analysis. The goal of PECAn is to streamline the interaction between data and models, and to improve the efficacy of scientific investigation.
Maintained by Istem Fer. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplantsjagscpp
216 stars 9.96 score 20 scripts 2 dependentspecanproject
PEcAn.priors:PEcAn Functions Used to Estimate Priors from Data
Functions to estimate priors from data.
Maintained by David LeBauer. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplantsjagscpp
216 stars 9.95 score 13 scripts 6 dependentspecanproject
PEcAn.MA:PEcAn Functions Used for Meta-Analysis
The Predictive Ecosystem Carbon Analyzer (PEcAn) is a scientific workflow management tool that is designed to simplify the management of model parameterization, execution, and analysis. The goal of PECAn is to streamline the interaction between data and models, and to improve the efficacy of scientific investigation. The PEcAn.MA package contains the functions used in the Bayesian meta-analysis of trait data.
Maintained by David LeBauer. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplantsjagscpp
216 stars 9.91 score 7 scripts 7 dependentspecanproject
PEcAnRTM:PEcAn Functions Used for Radiative Transfer Modeling
Functions for performing forward runs and inversions of radiative transfer models (RTMs). Inversions can be performed using maximum likelihood, or more complex hierarchical Bayesian methods. Underlying numerical analyses are optimized for speed using Fortran code.
Maintained by Alexey Shiklomanov. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplantsfortranjagscpp
216 stars 9.70 score 132 scriptspecanproject
PEcAn.remote:PEcAn Model Execution Utilities
This package contains utilities for communicating with and executing code on local and remote hosts. In particular, it has PEcAn-specific utilities for starting ecosystem model runs.
Maintained by Rob Kooper. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplants
216 stars 9.68 score 13 scripts 32 dependentspecanproject
PEcAn.logger:Logger Functions for 'PEcAn'
Convenience functions for logging outputs from 'PEcAn', the Predictive Ecosystem Analyzer (LeBauer et al. 2017) <doi:10.1890/12-0137.1>. Enables the user to set what level of messages are printed, as well as whether these messages are written to the console, a file, or both. It also allows control over whether severe errors should stop execution of the 'PEcAn' workflow; this allows strictness when debugging and lenience when running large batches of simulations that should not be terminated by errors in individual models. It is loosely based on the 'log4j' package.
Maintained by Rob Kooper. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplants
216 stars 9.66 score 7 scripts 40 dependents
mikewlcheung
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 27 days ago.
meta-analysismeta-analytic-semmissing-datamultilevel-modelsmultivariate-analysisstructural-equation-modelingstructural-equation-models
30 stars 9.43 score 208 scripts 1 dependentspecanproject
PEcAn.data.land:PEcAn Functions Used for Ecological Forecasts and Reanalysis
The Predictive Ecosystem Carbon Analyzer (PEcAn) is a scientific workflow management tool that is designed to simplify the management of model parameterization, execution, and analysis. The goal of PECAn is to streamline the interaction between data and models, and to improve the efficacy of scientific investigation.
Maintained by Mike Dietze. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplantsjagscpp
216 stars 9.34 score 19 scripts 10 dependentspecanproject
PEcAn.allometry:PEcAn Allometry Functions
Synthesize allometric equations or fit allometries to data.
Maintained by Mike Dietze. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplants
216 stars 9.12 score 34 scriptspecanproject
PEcAn.qaqc:QAQC
PEcAn integration and model skill testing
Maintained by David LeBauer. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplants
216 stars 9.06 score 5 scriptspecanproject
PEcAn.all:PEcAn Functions Used for Ecological Forecasts and Reanalysis
The Predictive Ecosystem Carbon Analyzer (PEcAn) is a scientific workflow management tool that is designed to simplify the management of model parameterization, execution, and analysis. The goal of PEcAn is to streamline the interaction between data and models, and to improve the efficacy of scientific investigation.
Maintained by David LeBauer. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplantsjagscpp
216 stars 9.01 score 266 scriptspecanproject
PEcAn.MAAT:PEcAn Package for Integration of the MAAT Model
This module provides functions to wrap the MAAT model into the PEcAn workflows.
Maintained by Shawn Serbin. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplants
216 stars 8.96 score 12 scriptspecanproject
PEcAn.BIOCRO:PEcAn Package for Integration of the BioCro Model
This module provides functions to link BioCro to PEcAn.
Maintained by David LeBauer. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplantsjagscpp
216 stars 8.95 score 23 scriptspecanproject
PEcAn.uncertainty:PEcAn Functions Used for Propagating and Partitioning Uncertainties in Ecological Forecasts and Reanalysis
The Predictive Ecosystem Carbon Analyzer (PEcAn) is a scientific workflow management tool that is designed to simplify the management of model parameterization, execution, and analysis. The goal of PECAn is to streamline the interaction between data and models, and to improve the efficacy of scientific investigation.
Maintained by David LeBauer. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplantsjagscpp
216 stars 8.94 score 15 scripts 5 dependentspecanproject
PEcAn.photosynthesis:PEcAn functions used for leaf-level photosynthesis calculations
The Predictive Ecosystem Carbon Analyzer (PEcAn) is a scientific workflow management tool that is designed to simplify the management of model parameterization, execution, and analysis. The goal of PECAn is to streamline the interaction between data and models, and to improve the efficacy of scientific investigation. The PEcAn.photosynthesis package contains functions used in the Hierarchical Bayesian calibration of the Farquhar et al 1980 model.
Maintained by Mike Dietze. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplantsjagscpp
216 stars 8.86 score 19 scriptspecanproject
PEcAn.emulator:Gausian Process Emulator
Implementation of a Gaussian Process model (both likelihood and bayesian approaches) for kriging and model emulation. Includes functions for sampling design and prediction.
Maintained by Mike Dietze. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplants
216 stars 8.84 score 1 scripts 6 dependentspecanproject
PEcAn.workflow:PEcAn Functions Used for Ecological Forecasts and Reanalysis
The Predictive Ecosystem Carbon Analyzer (PEcAn) is a scientific workflow management tool that is designed to simplify the management of model parameterization, execution, and analysis. The goal of PEcAn is to streamline the interaction between data and models, and to improve the efficacy of scientific investigation. This package provides workhorse functions that can be used to run the major steps of a PEcAn analysis.
Maintained by David LeBauer. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplantsjagscpp
216 stars 8.84 score 15 scripts 4 dependentspecanproject
PEcAn.data.remote:PEcAn Functions Used for Extracting Remote Sensing Data
PEcAn module for processing remote data. Python module requirements: requests, json, re, ast, panads, sys. If any of these modules are missing, install using pip install <module name>.
Maintained by Bailey Morrison. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplants
216 stars 8.76 score 6 scripts 5 dependentspecanproject
PEcAn.ED2:PEcAn Package for Integration of ED2 Model
The Predictive Ecosystem Carbon Analyzer (PEcAn) is a scientific workflow management tool that is designed to simplify the management of model parameterization, execution, and analysis. The goal of PECAn is to streamline the interaction between data and models, and to improve the efficacy of scientific investigation. This package provides functions to link the Ecosystem Demography Model, version 2, to PEcAn.
Maintained by Mike Dietze. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplantsjagscpp
216 stars 8.74 score 145 scriptspecanproject
PEcAn.SIPNET:PEcAn Functions Used for Ecological Forecasts and Reanalysis
The Predictive Ecosystem Carbon Analyzer (PEcAn) is a scientific workflow management tool that is designed to simplify the management of model parameterization, execution, and analysis. The goal of PECAn is to streamline the interaction between data and models, and to improve the efficacy of scientific investigation.
Maintained by Mike Dietze. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplantsjagscpp
216 stars 8.37 score 61 scriptspecanproject
PEcAn.LINKAGES:PEcAn Package for Integration of the LINKAGES Model
This module provides functions to link the (LINKAGES) to PEcAn.
Maintained by Ann Raiho. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplantsjagscpp
216 stars 8.35 score 59 scripts
zhanxw
seqminer:Efficiently Read Sequence Data (VCF Format, BCF Format, METAL Format and BGEN Format) into R
Integrate sequencing data (Variant call format, e.g. VCF or BCF) or meta-analysis results in R. This package can help you (1) read VCF/BCF/BGEN files by chromosomal ranges (e.g. 1:100-200); (2) read RareMETAL summary statistics files; (3) read tables from a tabix-indexed files; (4) annotate VCF/BCF files; (5) create customized workflow based on Makefile.
Maintained by Xiaowei Zhan. Last updated 6 months ago.
annotationbcfbgenmeta-analysisnext-generation-sequencingplinksequencingtabixvcfworkflowzlibbzip2libzstdsqlite3cpp
30 stars 8.29 score 111 scripts 6 dependents
psychmeta
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 10 months ago.
hacktoberfestmeta-analysispsychologypsychometricpsychometrics
59 stars 8.21 score 151 scriptspecanproject
PEcAnAssimSequential:PEcAn Functions Used for Ecological Forecasts and Reanalysis
The Predictive Ecosystem Carbon Analyzer (PEcAn) is a scientific workflow management tool that is designed to simplify the management of model parameterization, execution, and analysis. The goal of PECAn is to streamline the interaction between data and models, and to improve the efficacy of scientific investigation.
Maintained by Mike Dietze. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplantsjagscpp
216 stars 8.13 score 35 scripts
novartis
RBesT:R Bayesian Evidence Synthesis Tools
Tool-set to support Bayesian evidence synthesis. This includes meta-analysis, (robust) prior derivation from historical data, operating characteristics and analysis (1 and 2 sample cases). Please refer to Weber et al. (2021) <doi:10.18637/jss.v100.i19> for details on applying this package while Neuenschwander et al. (2010) <doi:10.1177/1740774509356002> and Schmidli et al. (2014) <doi:10.1111/biom.12242> explain details on the methodology.
Maintained by Sebastian Weber. Last updated 2 months ago.
bayesianclinicalhistorical-datameta-analysiscpp
23 stars 7.94 score 115 scripts 5 dependents
danheck
metaBMA:Bayesian Model Averaging for Random and Fixed Effects Meta-Analysis
Computes the posterior model probabilities for standard meta-analysis models (null model vs. alternative model assuming either fixed- or random-effects, respectively). These posterior probabilities are used to estimate the overall mean effect size as the weighted average of the mean effect size estimates of the random- and fixed-effect model as proposed by Gronau, Van Erp, Heck, Cesario, Jonas, & Wagenmakers (2017, <doi:10.1080/23743603.2017.1326760>). The user can define a wide range of non-informative or informative priors for the mean effect size and the heterogeneity coefficient. Moreover, using pre-compiled Stan models, meta-analysis with continuous and discrete moderators with Jeffreys-Zellner-Siow (JZS) priors can be fitted and tested. This allows to compute Bayes factors and perform Bayesian model averaging across random- and fixed-effects meta-analysis with and without moderators. For a primer on Bayesian model-averaged meta-analysis, see Gronau, Heck, Berkhout, Haaf, & Wagenmakers (2021, <doi:10.1177/25152459211031256>).
Maintained by Daniel W. Heck. Last updated 1 years ago.
bayesbayes-factorbayesian-inferenceevidence-synthesismeta-analysismodel-averagingstancpp
28 stars 7.75 score 54 scripts 4 dependentspecanproject
PEcAn.BASGRA:PEcAn Package for Integration of the BASGRA Model
This module provides functions to link the BASGRA model to PEcAn.
Maintained by Istem Fer. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplantsfortranglibc
216 stars 7.58 score 1 scriptspecanproject
PEcAn.data.mining:PEcAn Functions Used for Exploring Model Residuals and Structures
(Temporary description) PEcAn functions used for exploring model residuals and structures.
Maintained by Mike Dietze. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplants
216 stars 7.58 score 1 scriptspecanproject
PEcAn.PRELES:PEcAn Package for Integration of the PRELES Model
This module provides functions to run the PREdict Light use efficiency Evapotranspiration and Soil moisture (PRELES) model on the PEcAn project. The Predictive Ecosystem Carbon Analyzer (PEcAn) is a scientific workflow management tool designed to simplify the management of model parameterization,execution, and analysis. The goal of PECAn is to streamline the interaction between data and models, and to improve the efficacy of scientific investigation.
Maintained by Tony Gardella. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplants
216 stars 7.58 score 4 scriptspecanproject
PEcAn.STICS:PEcAn Package for Integration of the STICS Model
This module provides functions to link the STICS to PEcAn.
Maintained by Istem Fer. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplants
216 stars 7.58 scorepecanproject
PEcAn.ModelName:PEcAn Package for Integration of the ModelName Model
This module provides functions to link the (ModelName) to PEcAn.
Maintained by Jane Doe. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplants
216 stars 7.58 scorepecanproject
PEcAn.MAESPA:PEcAn Functions Used for Ecological Forecasts and Reanalysis using MAESPA
The Predictive Ecosystem Carbon Analyzer (PEcAn) is a scientific workflow management tool that is designed to simplify the management of model parameterization, execution, and analysis. The goal of PECAn is to streamline the interaction between data and models, and to improve the efficacy of scientific investigation.This package allows for MAESPA to be run through the PEcAN workflow.
Maintained by Tony Gardella. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplants
216 stars 7.58 score 2 scriptspecanproject
PEcAn.LDNDC:PEcAn package for integration of the LDNDC model
This module provides functions to link the (LDNDC) to PEcAn.
Maintained by Henri Kajasilta. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplantsjagscpp
216 stars 7.58 scorepecanproject
PEcAn.CABLE:PEcAn package for integration of the CABLE model
This module provides functions to link the (CABLE) to PEcAn.
Maintained by Tony Gardella. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplants
216 stars 7.58 scorepecanproject
PEcAn.SIBCASA:PEcAn Package for Integration of the SiBCASA Model
This module provides functions to link (SiBCASA) to PEcAn. It is a work in progress and is not yet fully functional.
Maintained by Rob Kooper. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplants
216 stars 7.58 scorepecanproject
PEcAn.CLM45:PEcAn Package for Integration of CLM4.5 Model
The Predictive Ecosystem Carbon Analyzer (PEcAn) is a scientific workflow management tool that is designed to simplify the management of model parameterization, execution, and analysis. The goal of PECAn is to streamline the interaction between data and models, and to improve the efficacy of scientific investigation. This package provides functions to link the Community Land Model, version 4.5, to PEcAn.
Maintained by Mike Dietze. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplants
216 stars 7.58 score 1 scriptspecanproject
PEcAn.LPJGUESS:PEcAn Package for Integration of the LPJ-GUESS Model
This module provides functions to link LPJ-GUESS to PEcAn.
Maintained by Istem Fer. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplantscpp
216 stars 7.58 score 1 scriptspecanproject
PEcAn.FATES:PEcAn Package for Integration of FATES Model
The Predictive Ecosystem Carbon Analyzer (PEcAn) is a scientific workflow management tool that is designed to simplify the management of model parameterization, execution, and analysis. The goal of PECAn is to streamline the interaction between data and models, and to improve the efficacy of scientific investigation. This package provides functions to link the FATES model to PEcAn.
Maintained by Mike Dietze. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplants
216 stars 7.58 score 6 scriptspecanproject
PEcAn.JULES:PEcAn Package for Integration of the JULES Model
This module provides functions to link the (JULES) to PEcAn.
Maintained by Mike Dietze. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplants
216 stars 7.58 scorepecanproject
PEcAn.GDAY:PEcAn Package for Integration of the GDAY Model
This module provides functions to link the GDAY model to PEcAn.
Maintained by Martin De Kauwe. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplants
216 stars 7.58 score 1 scriptspecanproject
PEcAn.DALEC:PEcAn Package for Integration of the DALEC Model
This module provides functions to link DALEC to PEcAn.
Maintained by Mike Dietze. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplants
216 stars 7.58 score 8 scriptspecanproject
PEcAn.dvmdostem:PEcAn Package for Integration of the Dvmdostem Model
This module provides functions to link the dvmdostem model to PEcAn.
Maintained by Tobey Carman. Last updated 1 days ago.
bayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationpecanplants
216 stars 7.58 score 3 scripts
smartdata-analysis-and-statistics
metamisc:Meta-Analysis of Diagnosis and Prognosis Research Studies
Facilitate frequentist and Bayesian meta-analysis of diagnosis and prognosis research studies. It includes functions to summarize multiple estimates of prediction model discrimination and calibration performance (Debray et al., 2019) <doi:10.1177/0962280218785504>. It also includes functions to evaluate funnel plot asymmetry (Debray et al., 2018) <doi:10.1002/jrsm.1266>. Finally, the package provides functions for developing multivariable prediction models from datasets with clustering (de Jong et al., 2021) <doi:10.1002/sim.8981>.
Maintained by Thomas Debray. Last updated 2 months ago.
meta-analysisprognosisprognostic-models
7 stars 7.48 score 102 scripts
wwiecek
baggr:Bayesian Aggregate Treatment Effects
Running and comparing meta-analyses of data with hierarchical Bayesian models in Stan, including convenience functions for formatting data, plotting and pooling measures specific to meta-analysis. This implements many models from Meager (2019) <doi:10.1257/app.20170299>.
Maintained by Witold Wiecek. Last updated 9 days ago.
bayesian-statisticsmeta-analysisquantile-regressionstantreatment-effectscpp
49 stars 7.24 score 88 scripts
fbartos
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 2 months ago.
meta-analysismodel-averagingpublication-biasjagsopenblascpp
9 stars 6.88 score 53 scriptsguido-s
metasens:Statistical Methods for Sensitivity Analysis in Meta-Analysis
The following methods are implemented to evaluate how sensitive the results of a meta-analysis are to potential bias in meta-analysis and to support Schwarzer et al. (2015) <DOI:10.1007/978-3-319-21416-0>, Chapter 5 'Small-Study Effects in Meta-Analysis': - Copas selection model described in Copas & Shi (2001) <DOI:10.1177/096228020101000402>; - limit meta-analysis by Rücker et al. (2011) <DOI:10.1093/biostatistics/kxq046>; - upper bound for outcome reporting bias by Copas & Jackson (2004) <DOI:10.1111/j.0006-341X.2004.00161.x>; - imputation methods for missing binary data by Gamble & Hollis (2005) <DOI:10.1016/j.jclinepi.2004.09.013> and Higgins et al. (2008) <DOI:10.1177/1740774508091600>; - LFK index test and Doi plot by Furuya-Kanamori et al. (2018) <DOI:10.1097/XEB.0000000000000141>.
Maintained by Guido Schwarzer. Last updated 17 days ago.
adjustmentmeta-analysispublication-biasrstudio
8 stars 6.01 score 53 scriptsguido-s
diagmeta:Meta-Analysis of Diagnostic Accuracy Studies with Several Cutpoints
Provides methods by Steinhauser et al. (2016) <DOI:10.1186/s12874-016-0196-1> for meta-analysis of diagnostic accuracy studies with several cutpoints.
Maintained by Guido Schwarzer. Last updated 6 months ago.
diagnostic-accuracy-studiesmeta-analysisrstudio
4 stars 5.15 score 10 scripts
thlytras
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
5 stars 4.70 score 3 scripts
aebilgrau
GMCM:Fast Estimation of Gaussian Mixture Copula Models
Unsupervised Clustering and Meta-analysis using Gaussian Mixture Copula Models.
Maintained by Anders Ellern Bilgrau. Last updated 3 years ago.
clusteringgaussian-mixture-modelsmeta-analysisrankunsupervised-cluster-analysisopenblascpp
15 stars 4.62 score 56 scripts
shixiangwang
metawho:Meta-Analytical Implementation to Identify Who Benefits Most from Treatments
A tool for implementing so called 'deft' approach (see Fisher, David J., et al. (2017) <DOI:10.1136/bmj.j573>) and model visualization.
Maintained by Shixiang Wang. Last updated 5 years ago.
deft-approachmeta-analysissubgroup-analysis
7 stars 4.54 score 9 scripts
magosil86
getmstatistic:Quantifying Systematic Heterogeneity in Meta-Analysis
Quantifying systematic heterogeneity in meta-analysis using R. The M statistic aggregates heterogeneity information across multiple variants to, identify systematic heterogeneity patterns and their direction of effect in meta-analysis. It's primary use is to identify outlier studies, which either show "null" effects or consistently show stronger or weaker genetic effects than average across, the panel of variants examined in a GWAS meta-analysis. In contrast to conventional heterogeneity metrics (Q-statistic, I-squared and tau-squared) which measure random heterogeneity at individual variants, M measures systematic (non-random) heterogeneity across multiple independently associated variants. Systematic heterogeneity can arise in a meta-analysis due to differences in the study characteristics of participating studies. Some of the differences may include: ancestry, allele frequencies, phenotype definition, age-of-disease onset, family-history, gender, linkage disequilibrium and quality control thresholds. See <https://magosil86.github.io/getmstatistic/> for statistical statistical theory, documentation and examples.
Maintained by Lerato E Magosi. Last updated 4 years ago.
getmstatisticgwasheartgenes214heterogeneitymeta-analysismstatisticoutlier-studiesstatasystematic-heterogeneity
3 stars 4.41 score 17 scripts
irissun
detectnorm:Detect Nonnormality in Meta-Analysis without Raw Data
Non-normality could greatly distort the meta-analytic results, according to the simulation in Sun and Cheung (2020) <doi: 10.3758/s13428-019-01334-x>. This package aims to detect non-normality for two independent groups with only limited descriptive statistics, including mean, standard deviation, minimum, and maximum.
Maintained by Rongwei Sun. Last updated 4 months ago.
1 stars 2.88 score 15 scripts
nomahi
dmetatools:Computational tools for meta-analysis of diagnostic accuracy test
Computational tools for meta-analysis of diagnostic accuracy test. This package enables computations of confidence interval for the AUC of summary ROC curve and some related AUC-based inference methods.
Maintained by Hisashi Noma. Last updated 3 years ago.
aucbootstrapdiagnostic-testsmeta-analysissummary-roc-curve
2.70 score 2 scripts