Showing 136 of total 136 results (show query)
jaredhuling
personalized:Estimation and Validation Methods for Subgroup Identification and Personalized Medicine
Provides functions for fitting and validation of models for subgroup identification and personalized medicine / precision medicine under the general subgroup identification framework of Chen et al. (2017) <doi:10.1111/biom.12676>. This package is intended for use for both randomized controlled trials and observational studies and is described in detail in Huling and Yu (2021) <doi:10.18637/jss.v098.i05>.
Maintained by Jared Huling. Last updated 3 years ago.
causal-inferenceheterogeneity-of-treatment-effectindividualized-treatment-rulespersonalized-medicineprecision-medicinesubgroup-identificationtreatment-effectstreatment-scoring
18.6 match 32 stars 7.38 score 125 scripts 1 dependents
drizopoulos
JMbayes2:Extended Joint Models for Longitudinal and Time-to-Event Data
Fit joint models for longitudinal and time-to-event data under the Bayesian approach. Multiple longitudinal outcomes of mixed type (continuous/categorical) and multiple event times (competing risks and multi-state processes) are accommodated. Rizopoulos (2012, ISBN:9781439872864).
Maintained by Dimitris Rizopoulos. Last updated 11 days ago.
competing-riskslongitudinal-analysismixed-modelsmulti-statepersonalized-medicineprecision-medicineprediction-modelsurvival-modelsopenblascppopenmp
15.0 match 84 stars 8.27 score 264 scripts 2 dependents
thomasjemielita
StratifiedMedicine:Stratified Medicine
A toolkit for stratified medicine, subgroup identification, and precision medicine. Current tools include (1) filtering models (reduce covariate space), (2) patient-level estimate models (counterfactual patient-level quantities, such as the conditional average treatment effect), (3) subgroup identification models (find subsets of patients with similar treatment effects), and (4) treatment effect estimation and inference (for the overall population and discovered subgroups). These tools can be customized and are directly used in PRISM (patient response identifiers for stratified medicine; Jemielita and Mehrotra 2019 <arXiv:1912.03337>. This package is in beta and will be continually updated.
Maintained by Thomas Jemielita. Last updated 3 years ago.
11.0 match 2 stars 4.73 score 27 scripts
chstock
DTComPair:Comparison of Binary Diagnostic Tests in a Paired Study Design
Comparison of the accuracy of two binary diagnostic tests in a "paired" study design, i.e. when each test is applied to each subject in the study.
Maintained by Christian Stock. Last updated 5 months ago.
clinical-epidemiologycomparative-analysisdiagnosisdiagnostic-accuracy-studiesdiagnostic-likelihood-ratiodiagnostic-testsmedicinepredictive-valuesensitivityspecificity
10.0 match 1 stars 5.07 score 47 scripts
smartdata-analysis-and-statistics
precmed:Precision Medicine
A doubly robust precision medicine approach to fit, cross-validate and visualize prediction models for the conditional average treatment effect (CATE). It implements doubly robust estimation and semiparametric modeling approach of treatment-covariate interactions as proposed by Yadlowsky et al. (2020) <doi:10.1080/01621459.2020.1772080>.
Maintained by Thomas Debray. Last updated 5 months ago.
11.8 match 4 stars 4.20 score 4 scripts
nt-williams
lmtp:Non-Parametric Causal Effects of Feasible Interventions Based on Modified Treatment Policies
Non-parametric estimators for casual effects based on longitudinal modified treatment policies as described in Diaz, Williams, Hoffman, and Schenck <doi:10.1080/01621459.2021.1955691>, traditional point treatment, and traditional longitudinal effects. Continuous, binary, categorical treatments, and multivariate treatments are allowed as well are censored outcomes. The treatment mechanism is estimated via a density ratio classification procedure irrespective of treatment variable type. For both continuous and binary outcomes, additive treatment effects can be calculated and relative risks and odds ratios may be calculated for binary outcomes. Supports survival outcomes with competing risks (Diaz, Hoffman, and Hejazi; <doi:10.1007/s10985-023-09606-7>).
Maintained by Nicholas Williams. Last updated 8 days ago.
causal-inferencecensored-datalongitudinal-datamachine-learningmodified-treatment-policynonparametric-statisticsprecision-medicinerobust-statisticsstatisticsstochastic-interventionssurvival-analysistargeted-learning
7.5 match 64 stars 6.37 score 91 scripts
yuanlonghu
immcp:Poly-Pharmacology Toolkit for Traditional Chinese Medicine Research
Toolkit for Poly-pharmacology Research of Traditional Chinese Medicine. Based on the biological descriptors and drug-disease interaction networks, it can analyze the potential poly-pharmacological mechanisms of Traditional Chinese Medicine and be used for drug-repositioning in Traditional Chinese Medicine.
Maintained by Yuanlong Hu. Last updated 2 years ago.
network-pharmacologypolypharmacologytraditional-chinese-medicine
10.5 match 5 stars 4.40 score 2 scripts
spedygiorgio
markovchain:Easy Handling Discrete Time Markov Chains
Functions and S4 methods to create and manage discrete time Markov chains more easily. In addition functions to perform statistical (fitting and drawing random variates) and probabilistic (analysis of their structural proprieties) analysis are provided. See Spedicato (2017) <doi:10.32614/RJ-2017-036>. Some functions for continuous times Markov chains depend on the suggested ctmcd package.
Maintained by Giorgio Alfredo Spedicato. Last updated 4 months ago.
ctmcdtmcmarkov-chainmarkov-modelr-programmingrcppopenblascpp
3.5 match 104 stars 12.78 score 712 scripts 4 dependents
openintrostat
openintro:Datasets and Supplemental Functions from 'OpenIntro' Textbooks and Labs
Supplemental functions and data for 'OpenIntro' resources, which includes open-source textbooks and resources for introductory statistics (<https://www.openintro.org/>). The package contains datasets used in our open-source textbooks along with custom plotting functions for reproducing book figures. Note that many functions and examples include color transparency; some plotting elements may not show up properly (or at all) when run in some versions of Windows operating system.
Maintained by Mine Çetinkaya-Rundel. Last updated 2 months ago.
3.5 match 240 stars 11.39 score 6.0k scripts
kjhealy
gssrdoc:Document General Social Survey Variable
The General Social Survey (GSS) is a long-running, mostly annual survey of US households. It is administered by the National Opinion Research Center (NORC). This package contains the a tibble with information on the survey variables, together with every variable documented as an R help page. For more information on the GSS see \url{http://gss.norc.org}.
Maintained by Kieran Healy. Last updated 11 months ago.
17.2 match 2.28 score 38 scripts
asancpt
caffsim:Simulation of Plasma Caffeine Concentrations by Using Population Pharmacokinetic Model
Simulate plasma caffeine concentrations using population pharmacokinetic model described in Lee, Kim, Perera, McLachlan and Bae (2015) <doi:10.1007/s00431-015-2581-x> and the package was published <doi:10.12793/tcp.2017.25.3.141>.
Maintained by Sungpil Han. Last updated 5 years ago.
caffeinemedicinemonte-carlo-simulationpharmacokineticspharmacometricstoxicology
10.0 match 9 stars 3.77 score 13 scripts
wviechtb
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 2 days ago.
3.4 match 30 stars 10.54 score 65 scripts 93 dependents
egeulgen
PANACEA:Personalized Network-Based Anti-Cancer Therapy Evaluation
Identification of the most appropriate pharmacotherapy for each patient based on genomic alterations is a major challenge in personalized oncology. 'PANACEA' is a collection of personalized anti-cancer drug prioritization approaches utilizing network methods. The methods utilize personalized "driverness" scores from 'driveR' to rank drugs, mapping these onto a protein-protein interaction network. The "distance-based" method scores each drug based on these scores and distances between drugs and genes to rank given drugs. The "RWR" method propagates these scores via a random-walk with restart framework to rank the drugs. The methods are described in detail in Ulgen E, Ozisik O, Sezerman OU. 2023. PANACEA: network-based methods for pharmacotherapy prioritization in personalized oncology. Bioinformatics <doi:10.1093/bioinformatics/btad022>.
Maintained by Ege Ulgen. Last updated 2 years ago.
drugnetwork-analysisoncologypersonalized-medicine
7.5 match 10 stars 4.70 score 3 scripts
levenc
posologyr:Individual Dose Optimization using Population Pharmacokinetics
Personalize drug regimens using individual pharmacokinetic (PK) and pharmacokinetic-pharmacodynamic (PK-PD) profiles. By combining therapeutic drug monitoring (TDM) data with a population model, 'posologyr' offers accurate posterior estimates and helps compute optimal individualized dosing regimens. The empirical Bayes estimates are computed following the method described by Kang et al. (2012) <doi:10.4196/kjpp.2012.16.2.97>.
Maintained by Cyril Leven. Last updated 6 days ago.
bayesianmodel-informed-precision-dosingpharmacokineticsprecision-medicinetherapeutic-drug-monitoring
7.5 match 12 stars 4.68 score 9 scripts
alanarnholt
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.
3.8 match 7 stars 9.11 score 1.3k scripts 6 dependents
thiyangtdata
MedLEA:Morphological and Structural Features of Medicinal Leaves
Contains a dataset of morphological and structural features of 'Medicinal LEAves (MedLEA)'. The features of each species is recorded by manually viewing the medicinal plant repository available at (<http://www.instituteofayurveda.org/plants/>). You can also download repository of leaf images of 1099 medicinal plants in Sri Lanka.
Maintained by Thiyanga S. Talagala. Last updated 2 years ago.
9.2 match 2.70 score 5 scripts
rfhb
ctrdata:Retrieve and Analyze Clinical Trials in Public Registers
A system for querying, retrieving and analyzing protocol- and results-related information on clinical trials from four public registers, the 'European Union Clinical Trials Register' ('EUCTR', <https://www.clinicaltrialsregister.eu/>), 'ClinicalTrials.gov' (<https://clinicaltrials.gov/> and also translating queries the retired classic interface), the 'ISRCTN' (<http://www.isrctn.com/>) and the 'European Union Clinical Trials Information System' ('CTIS', <https://euclinicaltrials.eu/>). Trial information is downloaded, converted and stored in a database ('PostgreSQL', 'SQLite', 'DuckDB' or 'MongoDB'; via package 'nodbi'). Documents in registers associated with trials can also be downloaded. Other functions implement trial concepts canonically across registers, identify deduplicated records, easily find and extract variables (fields) of interest even from complex nested data as used by the registers, merge variables and update queries. The package can be used for meta-analysis and trend-analysis of the design and conduct as well as of the results of clinical trials across registers.
Maintained by Ralf Herold. Last updated 8 hours ago.
clinical-dataclinical-researchclinical-studiesclinical-trialsctgovdatabaseduckdbmongodbnodbipostgresqlregistersqlitestudiestrial
3.0 match 45 stars 7.92 score 32 scripts
lightbluetitan
MedDataSets:Comprehensive Medical, Disease, Treatment, and Drug Datasets
Provides an extensive collection of datasets related to medicine, diseases, treatments, drugs, and public health. This package covers topics such as drug effectiveness, vaccine trials, survival rates, infectious disease outbreaks, and medical treatments. The included datasets span various health conditions, including AIDS, cancer, bacterial infections, and COVID-19, along with information on pharmaceuticals and vaccines. These datasets are sourced from the R ecosystem and other R packages, remaining unaltered to ensure data integrity. This package serves as a valuable resource for researchers, analysts, and healthcare professionals interested in conducting medical and public health data analysis in R.
Maintained by Renzo Caceres Rossi. Last updated 5 months ago.
4.0 match 8 stars 5.68 score 60 scripts
reside-ic
ids:Generate Random Identifiers
Generate random or human readable and pronounceable identifiers.
Maintained by Rich FitzJohn. Last updated 3 years ago.
1.7 match 94 stars 13.27 score 175 scripts 165 dependents
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 1 months ago.
meta-analysismodel-averagingpublication-biasjagsopenblascpp
2.9 match 9 stars 6.97 score 53 scripts
bioc
swfdr:Estimation of the science-wise false discovery rate and the false discovery rate conditional on covariates
This package allows users to estimate the science-wise false discovery rate from Jager and Leek, "Empirical estimates suggest most published medical research is true," 2013, Biostatistics, using an EM approach due to the presence of rounding and censoring. It also allows users to estimate the false discovery rate conditional on covariates, using a regression framework, as per Boca and Leek, "A direct approach to estimating false discovery rates conditional on covariates," 2018, PeerJ.
Maintained by Simina M. Boca. Last updated 5 months ago.
multiplecomparisonstatisticalmethodsoftware
3.1 match 3 stars 6.25 score 37 scripts
laperez
Clustering:Techniques for Evaluating Clustering
The design of this package allows us to run different clustering packages and compare the results between them, to determine which algorithm behaves best from the data provided. See Martos, L.A.P., García-Vico, Á.M., González, P. et al.(2023) <doi:10.1007/s13748-022-00294-2> "Clustering: an R library to facilitate the analysis and comparison of cluster algorithms.", Martos, L.A.P., García-Vico, Á.M., González, P. et al. "A Multiclustering Evolutionary Hyperrectangle-Based Algorithm" <doi:10.1007/s44196-023-00341-3> and L.A.P., García-Vico, Á.M., González, P. et al. "An Evolutionary Fuzzy System for Multiclustering in Data Streaming" <doi:10.1016/j.procs.2023.12.058>.
Maintained by Luis Alfonso Perez Martos. Last updated 11 months ago.
4.8 match 5 stars 4.04 score 7 scripts
mrc-ide
odin:ODE Generation and Integration
Generate systems of ordinary differential equations (ODE) and integrate them, using a domain specific language (DSL). The DSL uses R's syntax, but compiles to C in order to efficiently solve the system. A solver is not provided, but instead interfaces to the packages 'deSolve' and 'dde' are generated. With these, while solving the differential equations, no allocations are done and the calculations remain entirely in compiled code. Alternatively, a model can be transpiled to R for use in contexts where a C compiler is not present. After compilation, models can be inspected to return information about parameters and outputs, or intermediate values after calculations. 'odin' is not targeted at any particular domain and is suitable for any system that can be expressed primarily as mathematical expressions. Additional support is provided for working with delays (delay differential equations, DDE), using interpolated functions during interpolation, and for integrating quantities that represent arrays.
Maintained by Rich FitzJohn. Last updated 9 months ago.
1.6 match 106 stars 9.74 score 290 scripts 3 dependents
vimc
orderly:Lightweight Reproducible Reporting
Order, create and store reports from R. By defining a lightweight interface around the inputs and outputs of an analysis, a lot of the repetitive work for reproducible research can be automated. We define a simple format for organising and describing work that facilitates collaborative reproducible research and acknowledges that all analyses are run multiple times over their lifespans.
Maintained by Rich FitzJohn. Last updated 2 years ago.
1.6 match 117 stars 9.63 score 94 scripts 4 dependents
agbarnett
dobson:Data from the GLM Book by Dobson and Barnett
Example datasets from the book "An Introduction to Generalised Linear Models" (Year: 2018, ISBN:9781138741515) by Dobson and Barnett.
Maintained by Adrian Barnett. Last updated 6 years ago.
datasetsgeneralized-linear-models
3.5 match 3 stars 4.05 score 74 scriptsmrc-ide
orderly2:Orderly Next Generation
Distributed reproducible computing framework, adopting ideas from git, docker and other software. By defining a lightweight interface around the inputs and outputs of an analysis, a lot of the repetitive work for reproducible research can be automated. We define a simple format for organising and describing work that facilitates collaborative reproducible research and acknowledges that all analyses are run multiple times over their lifespans.
Maintained by Rich FitzJohn. Last updated 2 months ago.
1.5 match 8 stars 8.30 score 49 scripts 2 dependentsmrc-ide
malariasimulation:An individual based model for malaria
Specifies the latest and greatest malaria model.
Maintained by Giovanni Charles. Last updated 27 days ago.
1.5 match 16 stars 8.17 score 146 scriptsmrc-ide
dust:Iterate Multiple Realisations of Stochastic Models
An Engine for simulation of stochastic models. Includes support for running stochastic models in parallel, either with shared or varying parameters. Simulations are run efficiently in compiled code and can be run with a fraction of simulated states returned to R, allowing control over memory usage. Support is provided for building bootstrap particle filter for performing Sequential Monte Carlo (e.g., Gordon et al. 1993 <doi:10.1049/ip-f-2.1993.0015>). The core of the simulation engine is the 'xoshiro256**' algorithm (Blackman and Vigna <arXiv:1805.01407>), and the package is further described in FitzJohn et al 2021 <doi:10.12688/wellcomeopenres.16466.2>.
Maintained by Rich FitzJohn. Last updated 6 months ago.
1.6 match 18 stars 7.84 score 60 scripts 3 dependents
epiverse-trace
simulist:Simulate Disease Outbreak Line List and Contacts Data
Tools to simulate realistic raw case data for an epidemic in the form of line lists and contacts using a branching process. Simulated outbreaks are parameterised with epidemiological parameters and can have age-structured populations, age-stratified hospitalisation and death risk and time-varying case fatality risk.
Maintained by Joshua W. Lambert. Last updated 3 days ago.
epidemiologyepiverselinelistoutbreaks
1.5 match 9 stars 7.86 score 27 scriptsmrc-ide
rrq:Simple Redis Queue
Simple Redis queue in R.
Maintained by Rich FitzJohn. Last updated 4 months ago.
1.6 match 24 stars 7.40 score 14 scripts 3 dependentsmrc-ide
monty:Monte Carlo Models
Experimental sources for the next generation of mcstate, now called 'monty', which will support much of the old mcstate functionality but new things like better parameter interfaces, Hamiltonian Monte Carlo, and other features.
Maintained by Rich FitzJohn. Last updated 1 months ago.
1.6 match 3 stars 7.52 score 29 scripts 3 dependents
taylor-arnold
ctrialsgov:Query Data from U.S. National Library of Medicine's Clinical Trials Database
Tools to create and query database from the U.S. National Library of Medicine's Clinical Trials database <https://clinicaltrials.gov/>. Functions provide access a variety of techniques for searching the data using range queries, categorical filtering, and by searching for full-text keywords. Minimal graphical tools are also provided for interactively exploring the constructed data.
Maintained by Taylor Arnold. Last updated 3 years ago.
3.3 match 3.46 score 29 scriptsepiverse-trace
cleanepi:Clean and Standardize Epidemiological Data
Cleaning and standardizing tabular data package, tailored specifically for curating epidemiological data. It streamlines various data cleaning tasks that are typically expected when working with datasets in epidemiology. It returns the processed data in the same format, and generates a comprehensive report detailing the outcomes of each cleaning task.
Maintained by Karim Mané. Last updated 2 days ago.
data-cleaningepidemiologyepiverse
1.5 match 9 stars 7.44 score 19 scriptsmrc-ide
mcstate:Monte Carlo Methods for State Space Models
Implements Monte Carlo methods for state-space models such as 'SIR' models in epidemiology. Particle MCMC (pmcmc) and SMC2 methods are planned. This package is particularly designed to work with odin/dust models, but we will see how general it becomes.
Maintained by Rich FitzJohn. Last updated 9 months ago.
1.6 match 19 stars 7.08 score 87 scriptsmrc-ide
dust2:Next Generation dust
Experimental sources for the next generation of dust, which will properly adopt the particle filter, have support for partial parameter updates, support for multiple parameter sets and hopefully better GPU/MPI support.
Maintained by Rich FitzJohn. Last updated 9 days ago.
1.7 match 6.66 score 32 scripts 2 dependentsmrc-ide
context:Contexts for evaluating R expressions
Contexts for evaluating R expressions.
Maintained by Rich FitzJohn. Last updated 2 years ago.
1.7 match 5 stars 6.59 score 1.7k scripts 1 dependentsvimc
vaultr:Vault Client for Secrets and Sensitive Data
Provides an interface to a 'HashiCorp' vault server over its http API (typically these are self-hosted; see <https://www.vaultproject.io>). This allows for secure storage and retrieval of secrets over a network, such as tokens, passwords and certificates. Authentication with vault is supported through several backends including user name/password and authentication via 'GitHub'.
Maintained by Rich FitzJohn. Last updated 1 years ago.
1.6 match 24 stars 6.78 score 2 scripts 1 dependents
cli9
dipm:Depth Importance in Precision Medicine (DIPM) Method
An implementation by Chen, Li, and Zhang (2022) <doi: 10.1093/bioadv/vbac041> of the Depth Importance in Precision Medicine (DIPM) method in Chen and Zhang (2022) <doi:10.1093/biostatistics/kxaa021> and Chen and Zhang (2020) <doi:10.1007/978-3-030-46161-4_16>. The DIPM method is a classification tree that searches for subgroups with especially poor or strong performance in a given treatment group.
Maintained by Cai Li. Last updated 2 years ago.
10.7 match 1.00 scorebioc
GeneOverlap:Test and visualize gene overlaps
Test two sets of gene lists and visualize the results.
Maintained by António Miguel de Jesus Domingues, Max-Planck Institute for Cell Biology and Genetics. Last updated 5 months ago.
multiplecomparisonvisualization
1.6 match 6.43 score 266 scriptsmrc-ide
hipercow:High Performance Computing
Set up cluster environments and jobs. Moo.
Maintained by Rich FitzJohn. Last updated 11 days ago.
1.6 match 1 stars 6.53 score 45 scripts 1 dependents
miracum
DQAstats:Core Functions for Data Quality Assessment
Perform data quality assessment ('DQA') of electronic health records ('EHR'). Publication: Kapsner et al. (2021) <doi:10.1055/s-0041-1733847>.
Maintained by Lorenz A. Kapsner. Last updated 13 days ago.
1.5 match 9 stars 6.55 score 4 scripts 1 dependentsmrc-ide
dde:Solve Delay Differential Equations
Solves ordinary and delay differential equations, where the objective function is written in either R or C. Suitable only for non-stiff equations, the solver uses a 'Dormand-Prince' method that allows interpolation of the solution at any point. This approach is as described by Hairer, Norsett and Wanner (1993) <ISBN:3540604529>. Support is also included for iterating difference equations.
Maintained by Rich FitzJohn. Last updated 6 months ago.
1.6 match 15 stars 6.20 score 35 scripts 1 dependentsmrc-ide
odin2:Next generation odin
Temporary package for rewriting odin.
Maintained by Rich FitzJohn. Last updated 2 months ago.
1.6 match 5 stars 6.32 score 22 scriptsmrc-ide
cinterpolate:Interpolation From C
Simple interpolation methods designed to be used from C code. Supports constant, linear and spline interpolation. An R wrapper is included but this package is primarily designed to be used from C code using 'LinkingTo'. The spline calculations are classical cubic interpolation, e.g., Forsythe, Malcolm and Moler (1977) <ISBN: 9780131653320>.
Maintained by Rich FitzJohn. Last updated 6 months ago.
1.7 match 9 stars 5.77 score 1 scripts 4 dependents
cran
epiDisplay:Epidemiological Data Display Package
Package for data exploration and result presentation. Full 'epicalc' package with data management functions is available at '<https://medipe.psu.ac.th/epicalc/>'.
Maintained by Virasakdi Chongsuvivatwong. Last updated 3 years ago.
1.7 match 1 stars 5.44 score 758 scripts 2 dependentsmrc-ide
odin.dust:Compile Odin to Dust
Less painful than it sounds, this package compiles an odin model to use dust, our new stochastic model system. Supports only a subset of odin models (discrete time stochastic models with no interpolation and no delays).
Maintained by Rich FitzJohn. Last updated 6 months ago.
1.6 match 3 stars 5.71 score 122 scripts
jameel-institute
daedalus:Model Health, Social, and Economic Costs of a Pandemic
Model the health, education, and economic costs of directly transmitted respiratory virus pandemics, under different scenarios of prior vaccine investment and reactive interventions, using the 'DAEDALUS' integrated health-economics model adapted from Haw et al. (2022) <doi.org/10.1038/s43588-022-00233-0>.
Maintained by Pratik Gupte. Last updated 6 days ago.
decision-supportepidemiological-modelshealth-economicspandemic-preparednesspublic-healthrcppsdg-3cppopenmp
1.5 match 4 stars 5.92 score 8 scripts
emcramer
CHOIRBM:Plots the CHOIR Body Map
Collection of utility functions for visualizing body map data collected with the Collaborative Health Outcomes Information Registry.
Maintained by Eric Cramer. Last updated 1 years ago.
body-mapcbmchoirdata-visualizationvisualization
1.6 match 5 stars 5.51 score 26 scriptscran
BioPred:An R Package for Biomarkers Analysis in Precision Medicine
Provides functions for training extreme gradient boosting model using propensity score A-learning and weight-learning methods. For further details, see Liu et al. (2024) <doi:10.1093/bioinformatics/btae592>.
Maintained by Zihuan Liu. Last updated 4 months ago.
2.9 match 3.00 scoremiracum
DIZutils:Utilities for 'DIZ' R Package Development
Utility functions used for the R package development infrastructure inside the data integration centers ('DIZ') to standardize and facilitate repetitive tasks such as setting up a database connection or issuing notification messages and to avoid redundancy.
Maintained by Jonathan M. Mang. Last updated 4 months ago.
1.5 match 3 stars 5.03 score 5 scripts 2 dependentsbioc
r3Cseq:Analysis of Chromosome Conformation Capture and Next-generation Sequencing (3C-seq)
This package is used for the analysis of long-range chromatin interactions from 3C-seq assay.
Maintained by Supat Thongjuea. Last updated 5 months ago.
1.6 match 3 stars 4.85 score 17 scripts
struckma
dataquieR:Data Quality in Epidemiological Research
Data quality assessments guided by a 'data quality framework introduced by Schmidt and colleagues, 2021' <doi:10.1186/s12874-021-01252-7> target the data quality dimensions integrity, completeness, consistency, and accuracy. The scope of applicable functions rests on the availability of extensive metadata which can be provided in spreadsheet tables. Either standardized (e.g. as 'html5' reports) or individually tailored reports can be generated. For an introduction into the specification of corresponding metadata, please refer to the 'package website' <https://dataquality.qihs.uni-greifswald.de/VIN_Annotation_of_Metadata.html>.
Maintained by Stephan Struckmann. Last updated 6 days ago.
1.5 match 4.90 score 9 scripts
ganglilab
geneset:Get Gene Sets for Gene Enrichment Analysis
Gene sets are fundamental for gene enrichment analysis. The package 'geneset' enables querying gene sets from public databases including 'GO' (Gene Ontology Consortium. (2004) <doi:10.1093/nar/gkh036>), 'KEGG' (Minoru et al. (2000) <doi:10.1093/nar/28.1.27>), 'WikiPathway' (Marvin et al. (2020) <doi:10.1093/nar/gkaa1024>), 'MsigDb' (Arthur et al. (2015) <doi:10.1016/j.cels.2015.12.004>), 'Reactome' (David et al. (2011) <doi:10.1093/nar/gkq1018>), 'MeSH' (Ish et al. (2014) <doi:10.4103/0019-5413.139827>), 'DisGeNET' (Janet et al. (2017) <doi:10.1093/nar/gkw943>), 'Disease Ontology' (Lynn et al. (2011) <doi:10.1093/nar/gkr972>), 'Network of Cancer Genes' (Dimitra et al. (2019) <doi:10.1186/s13059-018-1612-0>) and 'COVID-19' (Maxim et al. (2020) <doi:10.21203/rs.3.rs-28582/v1>). Gene sets are stored in the list object which provides data frame of 'geneset' and 'geneset_name'. The 'geneset' has two columns of term ID and gene ID. The 'geneset_name' has two columns of terms ID and term description.
Maintained by Yunze Liu. Last updated 2 years ago.
enrichment-analysisgenegeneset-enrichment
1.5 match 9 stars 4.75 score 21 scripts 2 dependentsepiverse-trace
readepi:Read Data from Health Information Systems
Data import from several health information systems ('HIS'). The current version of the package covers 'HIS' such as 'MS SQL', 'MySQL', and 'PostGRESQL' servers, 'REDCap', 'DHIS2' and 'Fingertips'.
Maintained by Karim Mané. Last updated 9 months ago.
data-importepidemiologyepiversehealth-information-systems
1.5 match 6 stars 4.78 score 5 scripts
ropensci
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 25 days ago.
anthropometrygrowth-standardsintergrowthwho
1.5 match 4 stars 4.38 score 8 scriptsmiracum
DQAgui:Graphical User Interface for Data Quality Assessment
A graphical user interface (GUI) to the functions implemented in the R package 'DQAstats'. Publication: Mang et al. (2021) <doi:10.1186/s12911-022-01961-z>.
Maintained by Lorenz A. Kapsner. Last updated 1 months ago.
1.5 match 2 stars 4.15 score 10 scriptsmiracum
DIZtools:Lightweight Utilities for 'DIZ' R Package Development
Lightweight utility functions used for the R package development infrastructure inside the data integration centers ('DIZ') to standardize and facilitate repetitive tasks such as setting up a database connection or issuing notification messages and to avoid redundancy.
Maintained by Jonathan M. Mang. Last updated 1 years ago.
1.5 match 3 stars 4.13 score 2 scripts 3 dependentsmrc-ide
didehpc:DIDE HPC Support
Previous DIDE HPC support. Don't use this, use hipercow instead.
Maintained by Rich FitzJohn. Last updated 4 months ago.
1.6 match 10 stars 3.94 score 58 scriptsbioc
CINdex:Chromosome Instability Index
The CINdex package addresses important area of high-throughput genomic analysis. It allows the automated processing and analysis of the experimental DNA copy number data generated by Affymetrix SNP 6.0 arrays or similar high throughput technologies. It calculates the chromosome instability (CIN) index that allows to quantitatively characterize genome-wide DNA copy number alterations as a measure of chromosomal instability. This package calculates not only overall genomic instability, but also instability in terms of copy number gains and losses separately at the chromosome and cytoband level.
Maintained by Yuriy Gusev. Last updated 5 months ago.
softwarecopynumbervariationgenomicvariationacghmicroarraygeneticssequencing
1.5 match 4.08 score 2 scripts
kapelner
PTE:Personalized Treatment Evaluator
We provide inference for personalized medicine models. Namely, we answer the questions: (1) how much better does a purported personalized recommendation engine for treatments do over a business-as-usual approach and (2) is that difference statistically significant?
Maintained by Adam Kapelner. Last updated 6 years ago.
2.5 match 2.37 score 26 scripts
joundso
cleaR:Clean the R Console and Environment
Small package to clean the R console and the R environment with the call of just one function.
Maintained by Jonathan M. Mang. Last updated 1 years ago.
1.6 match 3.78 score 3 scripts 4 dependents
fbertran
plsRbeta:Partial Least Squares Regression for Beta Regression Models
Provides Partial least squares Regression for (weighted) beta regression models (Bertrand 2013, <http://journal-sfds.fr/article/view/215>) and k-fold cross-validation of such models using various criteria. It allows for missing data in the explanatory variables. Bootstrap confidence intervals constructions are also available.
Maintained by Frederic Bertrand. Last updated 2 years ago.
1.3 match 2 stars 4.34 score 22 scriptsjoundso
requiRements:Helper Package to Install Packages for R
Helper function to install packages for R using an external 'requirements.txt' or a string containing diverse packages from several resources like Github or CRAN.
Maintained by Jonathan M. Mang. Last updated 2 years ago.
1.6 match 9 stars 3.65 score 7 scripts
deisygysi
NetSci:Calculates Basic Network Measures Commonly Used in Network Medicine
Calculates network measures commonly used in Network Medicine. Measures such as the Largest Connected Component, the Relative Largest Connected Component, Proximity and Separation are calculated along with their statistical significance. Significance can be computed both using a degree-preserving randomization and non-degree preserving.
Maintained by Deisy Morselli Gysi. Last updated 5 months ago.
3.3 match 1.70 score 9 scriptsmrc-ide
hipercow.windows:DIDE HPC Support for Windows
Driver for using the DIDE windows cluster, via the hipercow package. Typically the user will install that package directly and this once they are requested to.
Maintained by Rich FitzJohn. Last updated 11 days ago.
1.6 match 1 stars 3.32 score 2 scripts
danny-ldc
RcmdrPlugin.EBM:Rcmdr Evidence Based Medicine Plug-in Package
Rcmdr plug-in GUI extension for Evidence Based Medicine medical indicators calculations (Sensitivity, specificity, absolute risk reduction, relative risk, ...).
Maintained by Daniel-Corneliu Leucuta. Last updated 9 years ago.
5.2 match 1.00 score 1 scriptsmrc-ide
orderly.db:Database Support for 'orderly2'
Access databases from 'orderly2' while running reports. Includes the basic 'SQL' support originally included in 'orderly' for establishing connections and setting up data for use within a report.
Maintained by Rich FitzJohn. Last updated 1 years ago.
1.7 match 3.00 score 1 scriptsstruckma
flexsiteboard:Breaks Single Page Applications from 'flexdashboard' in Multiple Files
A drop-in replacement for 'flexdashboard' 'Rmd' documents, which implements an after-knit-hook to split the generated single page application in one document per main section to reduce rendering load in the web browser displaying the document. Put all 'JavaScript' stuff needed in all sections before the first headline featuring navigation menu attributes. This package is experimental and maybe replaced by a solution inside 'flexdashboard'.
Maintained by Stephan Struckmann. Last updated 2 years ago.
1.6 match 3.00 score 1 scriptsmrc-ide
queuer:Queue Tasks
Queue tasks to number of backends.
Maintained by Rich FitzJohn. Last updated 2 years ago.
1.7 match 4 stars 2.78 score 4 scriptsvimc
orderlyweb:Orderly Support for 'OrderlyWeb'
Client for 'OrderlyWeb' for use from the 'orderly' package. Allows downloading of reports, running remote reports and other interaction with the remote report repository.
Maintained by Rich FitzJohn. Last updated 2 years ago.
1.7 match 2.78 score 1 scripts 1 dependents
modeloriented
survex:Explainable Machine Learning in Survival Analysis
Survival analysis models are commonly used in medicine and other areas. Many of them are too complex to be interpreted by human. Exploration and explanation is needed, but standard methods do not give a broad enough picture. 'survex' provides easy-to-apply methods for explaining survival models, both complex black-boxes and simpler statistical models. They include methods specific to survival analysis such as SurvSHAP(t) introduced in Krzyzinski et al., (2023) <doi:10.1016/j.knosys.2022.110234>, SurvLIME described in Kovalev et al., (2020) <doi:10.1016/j.knosys.2020.106164> as well as extensions of existing ones described in Biecek et al., (2021) <doi:10.1201/9780429027192>.
Maintained by Mikołaj Spytek. Last updated 9 months ago.
biostatisticsbrier-scorescensored-datacox-modelcox-regressionexplainable-aiexplainable-machine-learningexplainable-mlexplanatory-model-analysisinterpretable-machine-learninginterpretable-mlmachine-learningprobabilistic-machine-learningshapsurvival-analysistime-to-eventvariable-importancexai
0.5 match 110 stars 8.40 score 114 scriptsmrc-ide
testthat.buildkite:A testthat reporter for buildkite
A testthat reporter that prints progress output in a format for use in buildkite logs.
Maintained by Robert Ashton. Last updated 2 years ago.
1.7 match 2.54 score 1 scriptsmrc-ide
conan2:Conan the Librarian
Create libraries. For us, there is no spring. Just the wind that smells fresh before the storm.
Maintained by Rich FitzJohn. Last updated 17 days ago.
1.7 match 2.48 score 1 scripts 1 dependentsmrc-ide
threemc:(Matt's) Multi-Level Model of Male Circumcision in Sub-Saharan Africa
Functions and datasets to support, and extend to other Sub-Saharan African countries, Thomas, M. et. al., 2021, A multi-level model for estimating region-age-time-type specific male circumcision coverage from household survey and health system data in South Africa, <arXiv:2108.091422>.
Maintained by Patrick OToole. Last updated 1 years ago.
1.5 match 2.38 score 16 scriptsmrc-ide
mode:Solve Multiple ODEs
Solve multiple ODEs in parallel.
Maintained by Rich FitzJohn. Last updated 2 years ago.
1.6 match 2.10 score 25 scripts
bjw34032
oro.dicom:Rigorous - DICOM Input / Output
Data input/output functions for data that conform to the Digital Imaging and Communications in Medicine (DICOM) standard, part of the Rigorous Analytics bundle.
Maintained by Brandon Whitcher. Last updated 1 years ago.
0.5 match 1 stars 6.35 score 188 scripts 8 dependentsmrc-ide
heartbeatr:Heartbeat Support using 'Redis'
Simple heartbeat support for R using 'Redis'. A heartbeat is a background thread that acts as a dead-man's switch. It will create a key on Redis that will automatically expire after a number of seconds and then periodically refresh that key, even when the R process is busy. If the process dies for some reason, then the key will disappear. A heartbeat can be used to detect loss of worker processes on shared systems.
Maintained by Rich FitzJohn. Last updated 4 years ago.
1.7 match 2 stars 2.00 score 4 scriptsmrc-ide
orderly.sharedfile:Package Title Here
Access files in shared locations from orderly.
Maintained by Rich FitzJohn. Last updated 5 months ago.
1.7 match 1 stars 2.00 score 2 scriptsvimc
orderly.sharepoint:Sharepoint Driver for Orderly
Store orderly reports on Sharepoint. Provides an orderly remote driver that can be used to share orderly reports using Sharepoint. You can use Sharepoint's access controls and use this to set up a lightweight way of using orderly within a team.
Maintained by Rich FitzJohn. Last updated 2 years ago.
1.7 match 2.00 score 2 scripts
cran
CBCgrps:Compare Baseline Characteristics Between Groups
Compare baseline characteristics between two or more groups. The variables being compared can be factor and numeric variables. The function will automatically judge the type and distribution of the variables, and make statistical description and bivariate analysis.
Maintained by Zhongheng Zhang. Last updated 4 years ago.
1.6 match 1.98 score
piusdahinden
expirest:Expiry Estimation Procedures
The Australian Regulatory Guidelines for Prescription Medicines (ARGPM), guidance on "Stability testing for prescription medicines", recommends to predict the shelf life of chemically derived medicines from stability data by taking the worst case situation at batch release into account. Consequently, if a change over time is observed, a release limit needs to be specified. Finding a release limit and the associated shelf life is supported, as well as the standard approach that is recommended by guidance Q1E "Evaluation of stability data" from the International Council for Harmonisation (ICH).
Maintained by Pius Dahinden. Last updated 19 days ago.
0.9 match 3.40 score 6 scriptsjameel-institute
jameelinst.rpkg.theme:A 'pkgdown' Template for Jameel Institute Packages
Package website colours and logos taken from the Imperial College London and Jameel Institute brand guidelines.
Maintained by Pratik Gupte. Last updated 5 months ago.
1.6 match 2.00 score
myles-lewis
glmmSeq:General Linear Mixed Models for Gene-Level Differential Expression
Using mixed effects models to analyse longitudinal gene expression can highlight differences between sample groups over time. The most widely used differential gene expression tools are unable to fit linear mixed effect models, and are less optimal for analysing longitudinal data. This package provides negative binomial and Gaussian mixed effects models to fit gene expression and other biological data across repeated samples. This is particularly useful for investigating changes in RNA-Sequencing gene expression between groups of individuals over time, as described in: Rivellese, F., Surace, A. E., Goldmann, K., Sciacca, E., Cubuk, C., Giorli, G., ... Lewis, M. J., & Pitzalis, C. (2022) Nature medicine <doi:10.1038/s41591-022-01789-0>.
Maintained by Myles Lewis. Last updated 2 months ago.
bioinformaticsdifferential-gene-expressiongene-expressionglmmmixed-modelstranscriptomics
0.5 match 19 stars 6.11 score 45 scripts
vimc
orderly.rstudio:RStudio addins for orderly
RStudio addins for orderly.
Maintained by Robert Ashton. Last updated 4 years ago.
1.7 match 1 stars 1.70 score 1 scripts
biometrician
coxphw:Weighted Estimation in Cox Regression
Implements weighted estimation in Cox regression as proposed by Schemper, Wakounig and Heinze (Statistics in Medicine, 2009, <doi:10.1002/sim.3623>) and as described in Dunkler, Ploner, Schemper and Heinze (Journal of Statistical Software, 2018, <doi:10.18637/jss.v084.i02>). Weighted Cox regression provides unbiased average hazard ratio estimates also in case of non-proportional hazards. Approximated generalized concordance probability an effect size measure for clear-cut decisions can be obtained. The package provides options to estimate time-dependent effects conveniently by including interactions of covariates with arbitrary functions of time, with or without making use of the weighting option.
Maintained by Daniela Dunkler. Last updated 1 years ago.
cox-regressionsurvival-analysisfortran
0.5 match 1 stars 5.45 score 27 scripts 1 dependents
biogenies
countfitteR:Comprehensive Automatized Evaluation of Distribution Models for Count Data
A large number of measurements generate count data. This is a statistical data type that only assumes non-negative integer values and is generated by counting. Typically, counting data can be found in biomedical applications, such as the analysis of DNA double-strand breaks. The number of DNA double-strand breaks can be counted in individual cells using various bioanalytical methods. For diagnostic applications, it is relevant to record the distribution of the number data in order to determine their biomedical significance (Roediger, S. et al., 2018. Journal of Laboratory and Precision Medicine. <doi:10.21037/jlpm.2018.04.10>). The software offers functions for a comprehensive automated evaluation of distribution models of count data. In addition to programmatic interaction, a graphical user interface (web server) is included, which enables fast and interactive data-scientific analyses. The user is supported in selecting the most suitable counting distribution for his own data set.
Maintained by Jaroslaw Chilimoniuk. Last updated 2 years ago.
cancercancer-imaging-researchcount-datacount-distributionfoci
0.5 match 4 stars 5.33 score 27 scripts
marksendak
constellation:Identify Event Sequences Using Time Series Joins
Examine any number of time series data frames to identify instances in which various criteria are met within specified time frames. In clinical medicine, these types of events are often called "constellations of signs and symptoms", because a single condition depends on a series of events occurring within a certain amount of time of each other. This package was written to work with any number of time series data frames and is optimized for speed to work well with data frames with millions of rows.
Maintained by Mark Sendak. Last updated 6 years ago.
electronic-health-recordelectronic-health-recordshealthcarepatientstimeseries
0.5 match 6 stars 4.76 score 19 scripts
zjg540066169
AuxSurvey:Survey Analysis with Auxiliary Discretized Variables
Probability surveys often use auxiliary continuous data from administrative records, but the utility of this data is diminished when it is discretized for confidentiality. We provide a set of survey estimators to make full use of information from the discretized variables. See Williams, S.Z., Zou, J., Liu, Y., Si, Y., Galea, S. and Chen, Q. (2024), Improving Survey Inference Using Administrative Records Without Releasing Individual-Level Continuous Data. Statistics in Medicine, 43: 5803-5813. <doi:10.1002/sim.10270> for details.
Maintained by Jungang Zou. Last updated 3 months ago.
auxilary-variablescategorical-variablessurvey-analysis
0.5 match 1 stars 4.70 score 5 scriptsbioc
sitadela:An R package for the easy provision of simple but complete tab-delimited genomic annotation from a variety of sources and organisms
Provides an interface to build a unified database of genomic annotations and their coordinates (gene, transcript and exon levels). It is aimed to be used when simple tab-delimited annotations (or simple GRanges objects) are required instead of the more complex annotation Bioconductor packages. Also useful when combinatorial annotation elements are reuired, such as RefSeq coordinates with Ensembl biotypes. Finally, it can download, construct and handle annotations with versioned genes and transcripts (where available, e.g. RefSeq and latest Ensembl). This is particularly useful in precision medicine applications where the latter must be reported.
Maintained by Panagiotis Moulos. Last updated 5 months ago.
softwareworkflowsteprnaseqtranscriptionsequencingtranscriptomicsbiomedicalinformaticsfunctionalgenomicssystemsbiologyalternativesplicingdataimportchipseq
0.5 match 4.60 score 2 scripts
bioc
PathNet:An R package for pathway analysis using topological information
PathNet uses topological information present in pathways and differential expression levels of genes (obtained from microarray experiment) to identify pathways that are 1) significantly enriched and 2) associated with each other in the context of differential expression. The algorithm is described in: PathNet: A tool for pathway analysis using topological information. Dutta B, Wallqvist A, and Reifman J. Source Code for Biology and Medicine 2012 Sep 24;7(1):10.
Maintained by Ludwig Geistlinger. Last updated 5 months ago.
pathwaysdifferentialexpressionmultiplecomparisonkeggnetworkenrichmentnetwork
0.5 match 4.30 score 5 scripts
sidiwang
snSMART:Small N Sequential Multiple Assignment Randomized Trial Methods
Consolidated data simulation, sample size calculation and analysis functions for several snSMART (small sample sequential, multiple assignment, randomized trial) designs under one library. See Wei, B., Braun, T.M., Tamura, R.N. and Kidwell, K.M. "A Bayesian analysis of small n sequential multiple assignment randomized trials (snSMARTs)." (2018) Statistics in medicine, 37(26), pp.3723-3732 <doi:10.1002/sim.7900>.
Maintained by Michael Kleinsasser. Last updated 5 months ago.
bayesian-analysisclinical-trialsrare-diseasesmall-samplejagscpp
0.5 match 1 stars 3.90 score 3 scriptsbioc
ZygosityPredictor:Package for prediction of zygosity for variants/genes in NGS data
The ZygosityPredictor allows to predict how many copies of a gene are affected by small variants. In addition to the basic calculations of the affected copy number of a variant, the Zygosity-Predictor can integrate the influence of several variants on a gene and ultimately make a statement if and how many wild-type copies of the gene are left. This information proves to be of particular use in the context of translational medicine. For example, in cancer genomes, the Zygosity-Predictor can address whether unmutated copies of tumor-suppressor genes are present. Beyond this, it is possible to make this statement for all genes of an organism. The Zygosity-Predictor was primarily developed to handle SNVs and INDELs (later addressed as small-variants) of somatic and germline origin. In order not to overlook severe effects outside of the small-variant context, it has been extended with the assessment of large scale deletions, which cause losses of whole genes or parts of them.
Maintained by Marco Rheinnecker. Last updated 5 months ago.
biomedicalinformaticsfunctionalpredictionsomaticmutationgeneprediction
0.5 match 3.85 score 2 scripts
pboutros
ISOpureR:Deconvolution of Tumour Profiles
Deconvolution of mixed tumour profiles into normal and cancer for each patient, using the ISOpure algorithm in Quon et al. Genome Medicine, 2013 5:29. Deconvolution requires mixed tumour profiles and a set of unmatched "basis" normal profiles.
Maintained by Paul C Boutros. Last updated 6 years ago.
0.5 match 3 stars 3.61 score 34 scripts
fmmattioni
metabolic:Datasets and Functions for Reproducing Meta-Analyses
Dataset and functions from the meta-analysis published in Medicine & Science in Sports & Exercise. It contains all the data and functions to reproduce the analysis. "Effectiveness of HIIE versus MICT in Improving Cardiometabolic Risk Factors in Health and Disease: A Meta-analysis". Felipe Mattioni Maturana, Peter Martus, Stephan Zipfel, Andreas M Nieß (2020) <doi:10.1249/MSS.0000000000002506>.
Maintained by Felipe Mattioni Maturana. Last updated 1 years ago.
0.5 match 8 stars 3.60 score 8 scriptsbioc
SCAN.UPC:Single-channel array normalization (SCAN) and Universal exPression Codes (UPC)
SCAN is a microarray normalization method to facilitate personalized-medicine workflows. Rather than processing microarray samples as groups, which can introduce biases and present logistical challenges, SCAN normalizes each sample individually by modeling and removing probe- and array-specific background noise using only data from within each array. SCAN can be applied to one-channel (e.g., Affymetrix) or two-channel (e.g., Agilent) microarrays. The Universal exPression Codes (UPC) method is an extension of SCAN that estimates whether a given gene/transcript is active above background levels in a given sample. The UPC method can be applied to one-channel or two-channel microarrays as well as to RNA-Seq read counts. Because UPC values are represented on the same scale and have an identical interpretation for each platform, they can be used for cross-platform data integration.
Maintained by Stephen R. Piccolo. Last updated 5 months ago.
immunooncologysoftwaremicroarraypreprocessingrnaseqtwochannelonechannel
0.5 match 3.48 score 15 scripts
sth1402
DynTxRegime:Methods for Estimating Optimal Dynamic Treatment Regimes
Methods to estimate dynamic treatment regimes using Interactive Q-Learning, Q-Learning, weighted learning, and value-search methods based on Augmented Inverse Probability Weighted Estimators and Inverse Probability Weighted Estimators. Dynamic Treatment Regimes: Statistical Methods for Precision Medicine, Tsiatis, A. A., Davidian, M. D., Holloway, S. T., and Laber, E. B., Chapman & Hall/CRC Press, 2020, ISBN:978-1-4987-6977-8.
Maintained by Shannon T. Holloway. Last updated 1 years ago.
0.5 match 2 stars 3.44 score 115 scripts 2 dependentsbioc
RCASPAR:A package for survival time prediction based on a piecewise baseline hazard Cox regression model.
The package is the R-version of the C-based software \bold{CASPAR} (Kaderali,2006: \url{http://bioinformatics.oxfordjournals.org/content/22/12/1495}). It is meant to help predict survival times in the presence of high-dimensional explanatory covariates. The model is a piecewise baseline hazard Cox regression model with an Lq-norm based prior that selects for the most important regression coefficients, and in turn the most relevant covariates for survival analysis. It was primarily tried on gene expression and aCGH data, but can be used on any other type of high-dimensional data and in disciplines other than biology and medicine.
Maintained by Douaa Mugahid. Last updated 5 months ago.
acghgeneexpressiongeneticsproteomicsvisualization
0.5 match 3.30 score 1 scripts
gefeizhang
statVisual:Statistical Visualization Tools
Visualization functions in the applications of translational medicine (TM) and biomarker (BM) development to compare groups by statistically visualizing data and/or results of analyses, such as visualizing data by displaying in one figure different groups' histograms, boxplots, densities, scatter plots, error-bar plots, or trajectory plots, by displaying scatter plots of top principal components or dendrograms with data points colored based on group information, or visualizing volcano plots to check the results of whole genome analyses for gene differential expression.
Maintained by Wenfei Zhang. Last updated 5 years ago.
0.5 match 3.00 score 3 scripts
rbarkerclarke
gtexture:Generalized Application of Co-Occurrence Matrices and Haralick Texture
Generalizes application of gray-level co-occurrence matrix (GLCM) metrics to objects outside of images. The current focus is to apply GLCM metrics to the study of biological networks and fitness landscapes that are used in studying evolutionary medicine and biology, particularly the evolution of cancer resistance. The package was used in our publication, Barker-Clarke et al. (2023) <doi:10.1088/1361-6560/ace305>. A general reference to learn more about mathematical oncology can be found at Rockne et al. (2019) <doi:10.1088/1478-3975/ab1a09>.
Maintained by Rowan Barker-Clarke. Last updated 12 months ago.
0.5 match 3.00 score 1 scripts
yuande
tatest:Two-Group Ta-Test
The ta-test is a modified two-sample or two-group t-test of Gosset (1908). In small samples with less than 15 replicates,the ta-test significantly reduces type I error rate but has almost the same power with the t-test and hence can greatly enhance reliability or reproducibility of discoveries in biology and medicine. The ta-test can test single null hypothesis or multiple null hypotheses without needing to correct p-values.
Maintained by Yuan-De Tan. Last updated 3 years ago.
0.5 match 2.70 score 7 scripts
wanglabcsu
regverse:Streamlined Data Modeling and Visualization in Biomedical Regression Analysis
Provides a comprehensive suite of tools to enhance regression analysis and interpretation in the field of computational biology and clinical medicine.
Maintained by Shixiang Wang. Last updated 24 days ago.
0.5 match 2.30 score
andrew-leroux
fcr:Functional Concurrent Regression for Sparse Data
Dynamic prediction in functional concurrent regression with an application to child growth. Extends the pffr() function from the 'refund' package to handle the scenario where the functional response and concurrently measured functional predictor are irregularly measured. Leroux et al. (2017), Statistics in Medicine, <doi:10.1002/sim.7582>.
Maintained by Andrew Leroux. Last updated 7 years ago.
0.5 match 2.15 score 14 scripts
andrewyyp
tsriadditive:Two Stage Residual Inclusion Additive Hazards Estimator
Programs for A.Ying, R. Xu and J. Murphy. 'Two-Stage Residual Inclusion under the Additive Hazards Model - An Instrumental Variable Approach with Application to SEER-Medicare Linked Data.' Statistics in Medicine, to appear, 2018.
Maintained by Andrew Ying. Last updated 6 years ago.
0.5 match 2.00 score
nannikoski
rankhazard:Rank-Hazard Plots
Rank-hazard plots (Karvanen and Harrell, Statistics in Medicine 2009) visualize the relative importance of covariates in a proportional hazards model. The key idea is to rank the covariate values and plot the relative hazard as a function of ranks scaled to interval [0,1]. The relative hazard is plotted in respect to the reference hazard, which can bee.g. the hazard related to the median of the covariate.
Maintained by Nanni Koski. Last updated 9 years ago.
0.5 match 2.00 score 2 scripts
laylaparast
SBdecomp:Estimation of the Proportion of SB Explained by Confounders
Uses parametric and nonparametric methods to quantify the proportion of the estimated selection bias (SB) explained by each observed confounder when estimating propensity score weighted treatment effects. Parast, L and Griffin, BA (2020). "Quantifying the Bias due to Observed Individual Confounders in Causal Treatment Effect Estimates". Statistics in Medicine, 39(18): 2447- 2476 <doi: 10.1002/sim.8549>.
Maintained by Layla Parast. Last updated 3 years ago.
0.5 match 1 stars 2.00 score
cran
penAFT:Fit the Regularized Gehan Estimator with Elastic Net and Sparse Group Lasso Penalties
The semiparametric accelerated failure time (AFT) model is an attractive alternative to the Cox proportional hazards model. This package provides a suite of functions for fitting one popular estimator of the semiparametric AFT model, the regularized Gehan estimator. Specifically, we provide functions for cross-validation, prediction, coefficient extraction, and visualizing both trace plots and cross-validation curves. For further details, please see Suder, P. M. and Molstad, A. J., (2022+) Scalable algorithms for semiparametric accelerated failure time models in high dimensions, to appear in Statistics in Medicine <doi:10.1002/sim.9264>.
Maintained by Aaron J. Molstad. Last updated 2 years ago.
0.5 match 1.70 score 9 scriptscran
bayesSurv:Bayesian Survival Regression with Flexible Error and Random Effects Distributions
Contains Bayesian implementations of the Mixed-Effects Accelerated Failure Time (MEAFT) models for censored data. Those can be not only right-censored but also interval-censored, doubly-interval-censored or misclassified interval-censored. The methods implemented in the package have been published in Komárek and Lesaffre (2006, Stat. Modelling) <doi:10.1191/1471082X06st107oa>, Komárek, Lesaffre and Legrand (2007, Stat. in Medicine) <doi:10.1002/sim.3083>, Komárek and Lesaffre (2007, Stat. Sinica) <https://www3.stat.sinica.edu.tw/statistica/oldpdf/A17n27.pdf>, Komárek and Lesaffre (2008, JASA) <doi:10.1198/016214507000000563>, García-Zattera, Jara and Komárek (2016, Biometrics) <doi:10.1111/biom.12424>.
Maintained by Arnošt Komárek. Last updated 6 months ago.
0.5 match 1.69 score 49 scriptscran
cg:Compare Groups, Analytically and Graphically
Comprehensive data analysis software, and the name "cg" stands for "compare groups." Its genesis and evolution are driven by common needs to compare administrations, conditions, etc. in medicine research and development. The current version provides comparisons of unpaired samples, i.e. a linear model with one factor of at least two levels. It also provides comparisons of two paired samples. Good data graphs, modern statistical methods, and useful displays of results are emphasized.
Maintained by Bill Pikounis. Last updated 9 years ago.
0.5 match 1.60 scorecran
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.
0.5 match 1.48 score 1 dependents
danielegiardiello
raters:A Modification of Fleiss' Kappa in Case of Nominal and Ordinal Variables
The kappa statistic implemented by Fleiss is a very popular index for assessing the reliability of agreement among multiple observers. It is used both in the psychological and in the psychiatric field. Other fields of application are typically medicine, biology and engineering. Unfortunately,the kappa statistic may behave inconsistently in case of strong agreement between raters, since this index assumes lower values than it would have been expected. We propose a modification kappa implemented by Fleiss in case of nominal and ordinal variables. Monte Carlo simulations are used both to testing statistical hypotheses and to calculating percentile bootstrap confidence intervals based on proposed statistic in case of nominal and ordinal data.
Maintained by Daniele Giardiello. Last updated 6 months ago.
0.5 match 1.48 score 8 scripts
gsk3
bootLR:Bootstrapped Confidence Intervals for (Negative) Likelihood Ratio Tests
Computes appropriate confidence intervals for the likelihood ratio tests commonly used in medicine/epidemiology, using the method of Marill et al. (2015) <doi:10.1177/0962280215592907>. It is particularly useful when the sensitivity or specificity in the sample is 100%. Note that this does not perform the test on nested models--for that, see 'epicalc::lrtest'.
Maintained by Ari B. Friedman. Last updated 6 years ago.
0.5 match 1.30 score 7 scriptslaylaparast
cohetsurr:Assessing Complex Heterogeneity in Surrogacy
Provides functions to assess and test for complex heterogeneity in the utility of a surrogate marker with respect to multiple baseline covariates, using both a parametric model and a semiparametric two-step model. More details are available in: Knowlton, R., Tian, L., & Parast, L. (2025). "A General Framework to Assess Complex Heterogeneity in the Strength of a Surrogate Marker," Statistics in Medicine, 44(5), e70001 <doi:10.1002/sim.70001>. A tutorial for this package can be found at <https://laylaparast.com/home/cohetsurr.html>.
Maintained by Layla Parast. Last updated 10 days ago.
0.5 match 1.30 score
wimvde001
CorrMixed:Estimate Correlations Between Repeatedly Measured Endpoints (E.g., Reliability) Based on Linear Mixed-Effects Models
In clinical practice and research settings in medicine and the behavioral sciences, it is often of interest to quantify the correlation of a continuous endpoint that was repeatedly measured (e.g., test-retest correlations, ICC, etc.). This package allows for estimating these correlations based on mixed-effects models. Part of this software has been developed using funding provided from the European Union's 7th Framework Programme for research, technological development and demonstration under Grant Agreement no 602552.
Maintained by Wim Van der Elst. Last updated 3 years ago.
0.5 match 1.26 score 18 scriptswimvde001
EffectTreat:Prediction of Therapeutic Success
In personalized medicine, one wants to know, for a given patient and his or her outcome for a predictor (pre-treatment variable), how likely it is that a treatment will be more beneficial than an alternative treatment. This package allows for the quantification of the predictive causal association (i.e., the association between the predictor variable and the individual causal effect of the treatment) and related metrics. Part of this software has been developed using funding provided from the European Union's 7th Framework Programme for research, technological development and demonstration under Grant Agreement no 602552.
Maintained by Wim Van der Elst. Last updated 5 years ago.
0.5 match 1.15 score 14 scriptscran
nmadb:Network Meta-Analysis Database API
Set of functions for accessing database of network meta-analyses described in Petropoulou M, et al. Bibliographic study showed improving statistical methodology of network meta-analyses published between 1999 and 2015 <doi:10.1016/j.jclinepi.2016.11.002>. The database is hosted in a REDcap database at the Institute of Social and Preventive Medicine (ISPM) in the University of Bern.
Maintained by Theodoros Papakonstantinou. Last updated 5 years ago.
0.5 match 1.00 score 10 scripts
lirong95
LqG:Robust Group Variable Screening Based on Maximum Lq-Likelihood Estimation
Produces a group screening procedure that is based on maximum Lq-likelihood estimation, to simultaneously account for the group structure and data contamination in variable screening. The methods are described in Li, Y., Li, R., Qin, Y., Lin, C., & Yang, Y. (2021) Robust Group Variable Screening Based on Maximum Lq-likelihood Estimation. Statistics in Medicine, 40:6818-6834.<doi:10.1002/sim.9212>.
Maintained by Rong Li. Last updated 3 years ago.
0.5 match 1.00 scorecran
binomCI:Confidence Intervals for a Binomial Proportion
Twelve confidence intervals for one binomial proportion or a vector of binomial proportions are computed. The confidence intervals are: Jeffreys, Wald, Wald corrected, Wald, Blyth and Still, Agresti and Coull, Wilson, Score, Score corrected, Wald logit, Wald logit corrected, Arcsine and Exact binomial. References include, among others: Vollset, S. E. (1993). "Confidence intervals for a binomial proportion". Statistics in Medicine, 12(9): 809-824. <doi:10.1002/sim.4780120902>.
Maintained by Michail Tsagris. Last updated 4 months ago.
0.5 match 1 stars 1.00 score
imranshakoor
DataSetsUni:A Collection of Univariate Data Sets
A collection of widely used univariate data sets of various applied domains on applications of distribution theory. The functions allow researchers and practitioners to quickly, easily, and efficiently access and use these data sets. The data are related to different applied domains and as follows: Bio-medical, survival analysis, medicine, reliability analysis, hydrology, actuarial science, operational research, meteorology, extreme values, quality control, engineering, finance, sports and economics. The total 100 data sets are documented along with associated references for further details and uses.
Maintained by Muhammad Imran. Last updated 2 years ago.
0.5 match 1.00 score 1 scripts
ubcxzhang
bossR:Biomarker Optimal Segmentation System
The Biomarker Optimal Segmentation System R package, 'bossR', is designed for precision medicine, helping to identify individual traits using biomarkers. It focuses on determining the most effective cutoff value for a continuous biomarker, which is crucial for categorizing patients into two groups with distinctly different clinical outcomes. The package simultaneously finds the optimal cutoff from given candidate values and tests its significance. Simulation studies demonstrate that 'bossR' offers statistical power and false positive control non-inferior to the permutation approach (considered the gold standard in this field), while being hundreds of times faster.
Maintained by Xuekui Zhang. Last updated 1 years ago.
0.5 match 1.00 score
capanum
STOPES:Selection Threshold Optimized Empirically via Splitting
Implements variable selection procedures for low to moderate size generalized linear regressions models. It includes the STOPES functions for linear regression (Capanu M, Giurcanu M, Begg C, Gonen M, Optimized variable selection via repeated data splitting, Statistics in Medicine, 2020, 19(6):2167-2184) as well as subsampling based optimization methods for generalized linear regression models (Marinela Capanu, Mihai Giurcanu, Colin B Begg, Mithat Gonen, Subsampling based variable selection for generalized linear models).
Maintained by Marinela Capanu. Last updated 3 years ago.
0.5 match 1.00 score
ytstat
pemultinom:L1-Penalized Multinomial Regression with Statistical Inference
We aim for fitting a multinomial regression model with Lasso penalty and doing statistical inference (calculating confidence intervals of coefficients and p-values for individual variables). It implements 1) the coordinate descent algorithm to fit an l1-penalized multinomial regression model (parameterized with a reference level); 2) the debiasing approach to obtain the inference results, which is described in "Tian, Y., Rusinek, H., Masurkar, A. V., & Feng, Y. (2024). L1‐Penalized Multinomial Regression: Estimation, Inference, and Prediction, With an Application to Risk Factor Identification for Different Dementia Subtypes. Statistics in Medicine, 43(30), 5711-5747."
Maintained by Ye Tian. Last updated 16 days ago.
0.5 match 1.00 score 9 scriptscran
CoreMicrobiomeR:Identification of Core Microbiome
The Core Microbiome refers to the group of microorganisms that are consistently present in a particular environment, habitat, or host species. These microorganisms play a crucial role in the functioning and stability of that ecosystem. Identifying these microorganisms can contribute to the emerging field of personalized medicine. The 'CoreMicrobiomeR' is designed to facilitate the identification, statistical testing, and visualization of this group of microorganisms.This package offers three key functions to analyze and visualize microbial community data. This package has been developed based on the research papers published by Pereira et al.(2018) <doi:10.1186/s12864-018-4637-6> and Beule L, Karlovsky P. (2020) <doi:10.7717/peerj.9593>.
Maintained by Mohammad Samir Farooqi. Last updated 12 months ago.
0.5 match 1.00 score
chrislloyd58
CLAST:Exact Confidence Limits after a Sequential Trial
The user first provides design vectors n, a and b as well as null (p0) and alternative (p1) benchmark values for the probability of success. The key function "mv.plots.SM()" calculates mean values of exact upper and lower limits based on four different rank ordering methods. These plots form the basis of selecting a rank ordering. The function "inference()" calculates exact limits from a provided realisation and ordering choice. For more information, see "Exact confidence limits after a group sequential single arm binary trial" by Lloyd, C.J. (2020), Statistics in Medicine, Volume 38, 2389-2399, <doi:10.1002/sim.8909>.
Maintained by Chris J. Lloyd. Last updated 3 years ago.
0.5 match 1.00 score