Open Source R Psychometrics Projects

The psychmeta package provides tools for computing bare-bones and psychometric meta-analyses and for generating psychometric data for use in meta-analysis simulations. Currently, the package supports bare-bones, individual-correction, and artifact-distribution methods for meta-analyzing correlations and d values. Please refer to the overview tutorial vignette for an introduction to psychmeta’s functions and workflows. psychmeta is hosted on both CRAN and GitHub. Documentation for psychmeta’s functions is available in the package’s PDF manual. Includes tools for converting effect sizes, computing sporadic artifact corrections, reshaping meta-analytic databases, computing multivariate corrections for range variation, and more.

Estimating G-DINA model and a variety of widely-used models subsumed by the G-DINA model, including the DINA model, DINO model, additive-CDM (A-CDM), linear logistic model (LLM), reduced reparametrized unified model (RRUM), multiple-strategy DINA model for dichotomous responses. Estimating models within the G-DINA model framework using user-specified design matrix and link functions. Estimating Bugs-DINA, DINO and G-DINA models for dichotomous responses. Estimating sequential G-DINA model for ordinal and nominal responses. Estimating the generalized multiple-strategy cognitive diagnosis models (experimental). Estimating the diagnostic tree model (experimental). Estimating multiple-choice models. Modelling independent, saturated, higher-order, loglinear smoothed, and structured joint attribute distribution. Accommodating multiple-group model analysis. Imposing monotonic constrained success probabilities. Accommodating binary and polytomous attributes.

ShinyItemAnalysis is an R package including functions and interactive shiny application for the psychometric analysis of educational tests, psychological assessments, health-related and other types of multi-item measurements, or ratings from multiple raters. Exploration of total and standard scores. Analysis of measurement error and reliability. Analysis of correlation structure and validity. Traditional item analysis. Item analysis with regression models. Item analysis with IRT models. Detection of differential item functioning. Number of toy datasets is available, the interactive application also allows the users to upload and analyze their own data and to automatically generate PDF or HTML reports. All methods include sample R code which is ready to copy and paste into R and run locally. Several toy data sets are ready to use. You can also upload and analyze your own data. ShinyItemAnalysis provides model equations, parameter estimates and their interpretation.

blavaan is a free, open-source R package for Bayesian latent variable analysis. It relies on JAGS and Stan to estimate models via MCMC. The blavaan functions and syntax are similar to lavaan. The development version of blavaan (containing updates not yet on CRAN) can be installed via the command provided in the documentation. Compilation is required; this may be a problem for users who currently rely on a binary version of blavaan from CRAN. The blavaan package depends on the lavaan package for model specification and for some computations. This means that, if you already know lavaan, then you should already be able to do many things in blavaan. In particular, many blavaan commands add the letter “b” to the start of the lavaan command. It is also sometimes possible to use a lavaan command on a blavaan object, though the results may not always be what you expect.