Constructs tables of counts and proportions out of data sets with possibility to insert tables to Excel, Word, HTML, and PDF documents. Transforms tables to data suitable for modelling. Features Gibbs sampling based log-linear (NB2) and power analyses (original by Oleksandr Ocheredko <doi:10.35566/isdsa2019c5>) for tabulated data.
MCLogLin.R MCPower.R Plot.R PrintPower.R table_f.R
tableToData.R

Simulation-Based Bayesian Inference for Latent Traits of Item
Response Models
Functions for simulating realizations from the posterior distribution of
a latent trait of an item response model. Distributions are conditional on one or
a subset of response patterns (e.g., sum scores). Functions for computing likelihoods,
Fisher and observed information, posterior modes, and profile likelihood confidence
intervals are also included. These functions are designed to be easily amenable to
user-specified models.

coda, mcmcplots, ggmcmc, knitr, ggplot2, gridExtra, reshape2

Analysis of multivariate Bernoulli data using latent trait models (including the Rasch model) under the Item Response Theory approach.

Analysis of multivariate Bernoulli data using latent trait models (including the Rasch and the Two-Parameter Logistic models) under the Item Response Theory approach.

Analysis of multivariate Bernoulli and Ordinal data using latent trait models under the Item Response Theory approach.

Analysis of multivariate dichotomous and polytomous data using latent trait models under the Item Response Theory approach.

Analysis of multivariate dichotomous and polytomous data using latent trait models under the Item Response Theory approach. It includes the Rasch, the Two-Parameter Logistic, the Birnbaum's Three-Parameter, and the Graded Response Models.

R(>= 2.3.0), MASS, msm, mvtnorm, polycor

R (>= 2.3.0), MASS, msm, mvtnorm, polycor

Analysis of multivariate dichotomous and polytomous data using latent trait models under the Item Response Theory approach. It includes the Rasch, the Two-Parameter Logistic, the Birnbaum's Three-Parameter, the Graded Response, and the Generalized Partial Credit Models.
R (>= 2.5.0), MASS, msm, mvtnorm, polycor