Welcome!
Learn what you need to get started with measr and other r-dcm packages in four articles, starting with how to specify a diagnostic classification model (DCM) and ending with a beginning-to-end case study.
If you are new to diagnostic models
DCMs are a powerful psychometric tool for analyzing assessment data. The r-dcm suite of packages are designed to make the implementation of these models intuitive, and the documentation is focused on how to use the software. Before using these models in practice, we recommend that you start by learning the conceptual and statistical foundations of DCMs, then return here for information and tutorials on implementation. Here are some resources to start learning:
- Diagnostic Measurement Checklists, from the NCME ITEMS portal.
- Introduction to Diagnostic Classification Models, from the r-dcm team.
If you are new to R
The r-dcm packages are built in R and are designed to be compatible with the tidyverse. Therefore, in order to get the most of out r-dcm packages, we recommend that you start by learning some basics about R and the tidyverse first, then return here when you feel ready. Here are some resources to start learning:
- Finding Your Way to R, from the RStudio Education team.
- Learn the tidyverse, from the tidyverse team.