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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 |
Reference manual: | measr.pdf |
Vignettes: |
Getting started with measr measr: Bayesian psychometric measurement using Stan |
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 |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.