Specifying a DCM | Measurement models | Structural models | From specification to estimation | References
Package: dcmstan 0.1.0.9000
W. Jake Thompson
dcmstan: Generate 'Stan' Code for Diagnostic Classification Models
Diagnostic classification models are psychometric models used to categorically estimate respondents mastery, or proficiency, on a set of predefined skills (Bradshaw, 2016, <doi:10.1002/9781118956588.ch13>). 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.
Authors:
dcmstan_0.1.0.9000.tar.gz
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dcmstan_0.1.0.9000.tgz(r-4.6-any)dcmstan_0.1.0.9000.tgz(r-4.5-any)
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dcmstan_0.1.0.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
dcmstan/json (API)
| # Install 'dcmstan' in R: |
| install.packages('dcmstan', repos = c('https://r-dcm.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/r-dcm/dcmstan/issues
Pkgdown/docs site:https://dcmstan.r-dcm.org
Last updated from:c3297cabeb. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 219 | ||
| source / vignettes | OK | 228 | ||
| linux-release-x86_64 | OK | 230 | ||
| macos-release-arm64 | OK | 110 | ||
| macos-oldrel-arm64 | OK | 139 | ||
| windows-devel | OK | 143 | ||
| windows-release | OK | 148 | ||
| windows-oldrel | OK | 158 | ||
| wasm-release | OK | 140 |
Exports:bayesnetcreate_profilescrumdcm_specificationdcm_specifydcmpriordefault_dcm_priorsdinadinogenerated_quantitiesget_parametershdcmindependentlcdmloglinearncrumnidanidopriorprior_stringprior_tibblestan_codestan_dataunconstrained
Dependencies:base64encbitbit64bootcachemclicliprcpp11crayoncurldagittydplyrfarverfastmapforcatsgenericsggdagggforceggplot2ggraphggrepelgluegraphlayoutsgridExtragtablehmsigraphisobandjsonlitelabelinglatticelifecyclemagrittrMASSMatrixmemoisepillarpkgconfigpolyclipprettyunitsprogresspurrrR6RColorBrewerRcppRcppArmadillordcmchecksreadrrlangS7scalesstringistringrsystemfontstibbletidygraphtidyrtidyselecttweenrtzdbutf8V8vctrsviridisviridisLitevroomwithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Generate mastery profiles | create_profiles |
| S7 model specification class | dcm_specification |
| Specify a diagnostic classification model | dcm_specify |
| S7 prior class | dcmprior |
| Default priors for diagnostic classification models | default_dcm_priors |
| Generated quantities for diagnostic classification | generated-quantities generated_quantities |
| Identify parameters included in a diagnostic classification model | get_parameters |
| Measurement models for diagnostic classification | crum dina dino lcdm measurement-model ncrum nida nido |
| Prior definitions for diagnostic classification models | prior prior_string |
| Coerce a dcmprior object to a tibble | prior_tibble |
| Generate 'Stan' code for a diagnostic classification models | stan_code |
| Create a list of data objects for 'Stan' | stan_data |
| Structural models for diagnostic classification | bayesnet hdcm independent loglinear structural-model unconstrained |
