Man pages for wjakethompson/measr
Bayesian Psychometric Measurement Using 'Stan'
| as_measrfit | Coerce objects to a 'measrfit' |
| cdi | Item, attribute, and test-level discrimination indices |
| c.measrprior | Combine multiple measrprior objects into one measrprior |
| create_profiles | Generate mastery profiles |
| default_dcm_priors | Default priors for diagnostic classification models |
| ecpe | Examination for the Certificate of Proficiency in English |
| fit_m2 | Estimate the M_2 fit statistic for diagnostic classification... |
| fit_ppmc | Posterior predictive model checks for assessing model fit |
| get_parameters | Get a list of possible parameters |
| is_measrfit | Check if argument is a 'measrfit' object |
| is_measrprior | Checks if argument is a 'measrprior' object |
| loglik_array | Extract the log-likelihood of an estimated model |
| loo_compare.measrfit | Relative model fit comparisons |
| loo.measrfit | Efficient approximate leave-one-out cross-validation (LOO) |
| mdm | MacReady & Dayton (1977) multiplication data |
| measr_dcm | Fit Bayesian diagnostic classification models |
| measr_examples | Determine if code is executed interactively or in pkgdown |
| measr_extract | Extract components of a 'measrfit' object |
| measrfit | Create a 'measrfit' object |
| measrfit-class | Class 'measrfit' of models fitted with the measr package |
| measr-package | measr: Bayesian Psychometric Measurement Using 'Stan' |
| measrprior | Prior definitions for measr models |
| model_evaluation | Add model evaluation metrics model objects |
| pipe | Pipe operator |
| predict.measrdcm | Posterior draws of respondent proficiency |
| reexports | Objects exported from other packages |
| reliability | Estimate the reliability of psychometric models |
| tidyeval | Tidy eval helpers |
| waic.measrfit | Widely applicable information criterion (WAIC) |
