Latent Trait Models under IRT (ltm)
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.
Tools for Discrete Multivariate Mixed Membership Models (mixedMem)
Fits mixed membership models with discrete multivariate data (with or without repeated measures) following the general framework of Erosheva 2004. This package uses a Variational EM approach by approximating the posterior distribution of latent memberships and selecting hyperparameters through a pseudo-MLE procedure. Currently supported data types are Bernoulli, multinomial and rank (Plackett-Luce).
Average and Conditional Effects (EffectLiteR)
Use structural equation modeling to estimate average and conditional effects of a treatment variable on an outcome variable, taking into account multiple continuous and categorical covariates.