Links
R Project (Statistical Software)
Contributed R packages: CRAN (overview, sorted by date) | R Forge | CRAN Upload | winbuilder | CRAN pretest
CRANberries: New and updated packages on CRAN | github CRAN
Rtools: Building R packages for Windows
R Editors: RWinEdt | RStudio | Notepad++ (NpptoR)
R Ressources: Quick-R | R Seek | Rdocumentation |
Rcpp, RcppGallery, RcppArmadillo, Armadillo,
General Purpose Statistical Software / Bayesian Modeling
WinBUGS: Bayesian inference using Gibbs sampling | R2WinBUGS: Running WinBUGS from R
OpenBUGS: Open source version of WinBUGS | rbugs, R2OpenBUGS: Running OpenBUGS from R
JAGS: Just another Gibbs Sampler | R2jags, rjags and runjags: Running JAGS from R
NIMBLE: An R package for programming with BUGS models and compiling parts of R
stan: C++ library for probability and sampling | Rstan
admb: AD model builder | admb IDE | Working with admb and R | admb examples
Running admb from within R: PBSadmb, R2admb
TMB: Template model builder
Item Response Models
R Packages
More R Packages: mlirt, cirt, irtoys, psych, eat, plfm, , bfa, sbgcop, multicon, dualScale, mirtCAT, ltbayes, poLCA, randomLCA, mixedMem, SparseFactorAnalysis, logisticPCA, svs, FMP, ordinal, KernSmoothIRT,
Other IRT Software
ICL: IRT Command Language (B. Hanson)
NOHARM: McDonald's multidimensional normal ogive item response model
* Running NOHARM from R (in sirt)
Ressources
Psychometrics in R (W. Revelle)
Software for Rasch Modeling
Missing Data
mice: Multiple imputation by chained equations (GitHub)
pan: Multiple imputation for hierarchical data
jomo: Multilevel joint modeling multiple imputation
Zelig: Statistical analysis for multiply imputed and matched data sets
SensMice: Sensitivity analysis under Missing Not At Random (MNAR) assumption in mice
More R Packages
Amelia, Hmisc::AregImpute, BaBooN, cat, mi, mitools, mix, norm, VIM, countimp, MissMech,NPBayesImpute, smcfcs, midastouch, MixedDataImpute, MixRF, norm2, imputeMulti,
Own R packages: miceadds,
Other Software Packages
REALCOM-Impute: Multilevel imputation
Resources
Multilevel Modeling
R Packages
Generalized linear mixed effects models: lme4, nlme, arm, LMERConvenienceFunctions
MCMCglmm: Bayesian generalized linear mixed effects models
Generalized estimating equations (GEE): gee, geepack, yags
Cluster robust standard errors: rms::robcov, multiwaycov, clusterSEs
R-INLA: Integrated nested Laplace approximation in R
More R packages: amer, blme, gamm4, glmmAK, glmmadmb, glmmBUGS, HGLMMM, hglm, lmec, lmm,MEMSS, mlmRev, mlmmm, multilevel, regress, sabreR, mixcat, HLMdiag, minque, iccbeta, mixor, mbest,
Other Software Packages
aML: Multilevel, multiprocess models
MLA: Multilevel analysis for two levels
GENOVA: Generalizability theory (Variance component models)
MIXREG - MIXOR - MIXNO - MIXPREG: Mixed models for normal, ordinal and categorical data
Eugene Demidenko: Mixed Effects Models in R
Resources: GLMM FAQ,
Causal Inference
Matching Methods
MatchIt: Wide variety of matching algorithms
cem: Coarsed exact matching
optmatch: Optimal matching
twang: Weighting and analysis of nonequivalent groups
Matching: Multivariate and propensity score matching with balance optimization
nonrandom: Stratification and matching by the propensity score
CBPS: Covariate balancing propensity score
ebal: Entropy balancing
PSAgraphics: Graphics for propensity score analysis
Mediation Analysis
mediation: Causal mediation analysis
Sensitivity Analysis
obsSens: Sensitivity analysis for observational studies
SBSA: Simplied Bayesian sensitivity analysis
sensitivityPStrat: Principal stratification sensitivity analysis functions
Survey Analysis
R survey package (Homepage of T. Lumley) (on CRAN)
R packages: intsvy, svyPVpack, EVER, synthpop,
Own R packages: BIFIEsurvey,
CRAN Task View Survey Methodology
Latent Class Analysis & Mixture Modeling
lem: Analysis of categorical data (J. Vermunt)
MDLV: MATLAB Toolbox - Models with Discrete Latent Variables for Analysis of Categorical Data
R packages: covLCA, poLCA, randomLCA, BayesLCA, Rmixmod, lcmm, depmix,
Graphical Modeling
CRAN Task View Graphical Modeling
State Space Models
MKFM6: Program for Multi-Subject State Space Modeling (C. Dolan)
DyFA: Dynamic factor analysis (M. Browne)
HLGSSM: Hierarchical state space approach (T. Lodewyckx)
Computer Algebra Systems
Sage: Mission: Creating a viable free open source alternative to Magma, Maple, Mathematica and Matlab.
Python Programming language | rPython
SymPy Python library for symbolic mathematics | rSymPy
SPSS Substitutes
PSPP as an SPSS replacement
ViewSav: Viewing SPSS files
LATEX
Misc