The Transition Diagnostic Classification Model Framework

Estimate the transition diagnostic classification model (TDCM) described in Madison & Bradshaw (2018) , a longitudinal extension of the log-linear cognitive diagnosis model (LCDM) in Henson, Templin & Willse (2009) . As the LCDM subsumes many other diagnostic classification models (DCMs), many other DCMs can be estimated longitudinally via the TDCM. The 'TDCM' package includes functions to estimate the single-group and multigroup TDCM, summarize results of interest including item parameters, growth proportions, transition probabilities, transitional reliability, attribute correlations, model fit, and growth plots.

TDCM

The ‘TDCM’ R package lets users estimate the transition diagnostic classification model (TDCM) described in Madison & Bradshaw (2018), a longitudinal extension of the log-linear cognitive diagnosis model (LCDM) in Henson, Templin & Willse (2009). As the LCDM subsumes many other diagnostic classification models (DCMs), many other DCMs can be estimated longitudinally via the TDCM framework. The ‘TDCM’ package includes functions to estimate the single-group and multigroup TDCM, summarize results of interest including item parameters, growth proportions, transition probabilities, transitional reliability, attribute correlations, model fit, and growth plots.

Installation

You can install the ‘TDCM’ package like so:

# Install TDCM from CRAN
install.packages("TDCM")

# Install the latest development version of TDCM from GitHub:
if (!require("devtools")) install.packages("devtools")
devtools::install_github("cotterell/tdcm")

Getting Started

See vignette("TDCM", package = "TDCM") or for an overview of the ‘TDCM’ package.