measr: Bayesian Psychometric Measurement Using 'Stan'

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) <doi:10.1007/s11336-008-9089-5> 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.

Version:	1.0.0
Depends:	R (≥ 4.1.0)
Imports:	dcm2, dplyr (≥ 1.1.1), fs, glue, loo, magrittr, methods, posterior, psych, Rcpp (≥ 0.12.0), RcppParallel (≥ 5.0.1), rlang (≥ 0.4.11), rstan (≥ 2.26.0), rstantools (≥ 2.3.0), stats, tibble, tidyr (≥ 1.3.0)
LinkingTo:	BH (≥ 1.66.0), Rcpp (≥ 0.12.0), RcppEigen (≥ 0.3.3.3.0), RcppParallel (≥ 5.0.1), rstan (≥ 2.26.0), StanHeaders (≥ 2.26.0)
Suggests:	cli, cmdstanr (≥ 0.4.0), crayon, knitr, rmarkdown, roxygen2, spelling, testthat (≥ 3.0.0)
Published:	2024-01-30
DOI:	10.32614/CRAN.package.measr
Author:	W. Jake Thompson [aut, cre], Nathan Jones [ctb], Matthew Johnson [cph] (Provided code adapted for reliability.measrdcm()), Paul-Christian Bürkner [cph] (Author of eval_silent()), University of Kansas [cph], Institute of Education Sciences [fnd]
Maintainer:	W. Jake Thompson <wjakethompson at gmail.com>
BugReports:	https://github.com/wjakethompson/measr/issues
License:	GPL (≥ 3)
URL:	https://measr.info, https://github.com/wjakethompson/measr
NeedsCompilation:	yes
SystemRequirements:	GNU make
Additional_repositories:	https://mc-stan.org/r-packages/
Language:	en-US
Citation:	measr citation info
Materials:	README NEWS
CRAN checks:	measr results

Documentation:

Reference manual:	measr.pdf
Vignettes:	Getting started with measr measr: Bayesian psychometric measurement using Stan

Downloads:

Package source:	measr_1.0.0.tar.gz
Windows binaries:	r-devel: measr_1.0.0.zip, r-release: measr_1.0.0.zip, r-oldrel: measr_1.0.0.zip
macOS binaries:	r-release (arm64): measr_1.0.0.tgz, r-oldrel (arm64): measr_1.0.0.tgz, r-release (x86_64): measr_1.0.0.tgz, r-oldrel (x86_64): measr_1.0.0.tgz
Old sources:	measr archive

Linking:

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