r-dcm.r-universe.dev

[r-dcm] measr 2.0.1.9000

wjakethompson@gmail.com (W. Jake Thompson) — Wed, 01 Apr 2026 01:19:04 GMT

Estimate diagnostic classification models (also called cognitive diagnostic models) with 'Stan'. Diagnostic classification models are confirmatory latent class models, as described by Rupp et al. (2010, ISBN: 978-1-60623-527-0). Automatically generate 'Stan' code for the general loglinear cognitive diagnostic diagnostic model proposed by Henson et al. (2009) and other subtypes that introduce additional model constraints. Using the generated 'Stan' code, estimate the model evaluate the model's performance using model fit indices, information criteria, and reliability metrics.

[r-dcm] rdcmchecks 0.1.1.9000

wjakethompson@gmail.com (W. Jake Thompson) — Thu, 12 Mar 2026 00:54:21 GMT

Many packages in the 'r-dcm' family take similar arguments, which are checked for expected structures and values. Rather than duplicating code across several packages, commonly used check functions are included here. This package can then be imported to access the check functions in other packages.

[r-dcm] dcmdata 0.2.0.9000

wjakethompson@gmail.com (W. Jake Thompson) — Wed, 11 Mar 2026 17:27:01 GMT

Access data sets for demonstrating or testing diagnostic classification models. Simulated data sets can be used to compare estimated model output to true data-generating values. Real data sets can be used to demonstrate real-world applications of diagnostic models.

[r-dcm] dcmstan 0.1.0.9000

wjakethompson@gmail.com (W. Jake Thompson) — Tue, 02 Dec 2025 15:57:05 GMT

Diagnostic classification models are psychometric models used to categorically estimate respondents mastery, or proficiency, on a set of predefined skills (Bradshaw, 2016, ). Diagnostic models can be estimated with 'Stan'; however, the necessary scripts can be long and complicated. This package automates the creation of 'Stan' scripts for diagnostic classification models. Specify different types of diagnostic models, define prior distributions, and automatically generate the necessary 'Stan' code for estimating the model.