TDCM: An R Package for Estimating Longitudinal Diagnostic Classification Models

Diagnostic classification models (DCMs) are psychometric models designed to classify examinees according to their proficiency or non-proficiency of specified latent attributes. Longitudinal DCMs have recently been developed as psychometric models for modeling changes in examinee proficiency statuses over time. Currently, software programs for estimating longitudinal DCMs are limited in functionality and generality, expensive, or cumbersome for applied researchers. This manuscript describes and demonstrates a newly developed R package for estimating a general longitudinal DCM, the transition diagnostic classification model.