Bayesian Psychometric Measurement Using 'Stan'

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Documentation for package ‘measr’ version 2.0.0

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add_criterion Add model evaluation metrics model objects
add_fit Add model evaluation metrics model objects
add_reliability Add model evaluation metrics model objects
add_respondent_estimates Add model evaluation metrics model objects
aic Maximum likelihood based information criteria
bayes_factor Bayes factor for model comparisons
bic Maximum likelihood based information criteria
cdi Item, attribute, and test-level discrimination indices
cmdstanr S7 classes for estimation specifications
dcm_estimate Fit Bayesian diagnostic classification models
fit_m2.measr::measrdcm Estimate the M_2 fit statistic for diagnostic classification models
fit_ppmc Posterior predictive model checks for assessing model fit
gqs S7 classes for estimation specifications
loglik_array Extract the log-likelihood of an estimated model
log_mll Log marginal likelihood calculation
loo-waic Relative fit for Bayesian models
loo.measr::measrdcm Relative fit for Bayesian models
loo_compare.measr::measrdcm Relative fit for Bayesian models
m2 Estimate the M_2 fit statistic for diagnostic classification models
mcmc S7 classes for estimation specifications
measrdcm S7 class for measrdcm objects
measr_examples Determine if code is executed interactively or in pkgdown
measr_extract Extract components of a 'measrfit' object
model_evaluation Add model evaluation metrics model objects
optim S7 classes for estimation specifications
pathfinder S7 classes for estimation specifications
qmatrix_validation Q-matrix validation
reliability Estimate the reliability of a diagnostic classification model
rstan S7 classes for estimation specifications
score Posterior draws of respondent proficiency
stan-classes S7 classes for estimation specifications
variational S7 classes for estimation specifications
waic.measr::measrdcm Relative fit for Bayesian models
yens_q3 Yen's Q_3 statistic for local item dependence