Package: classicaltest 0.7.5
Andrés Christiansen
classicaltest: Classical Test Theory (CTT) Analysis
Functions for classical test theory analysis, following methods presented by Wu et al. (2006) <doi:10.1007/978-981-10-3302-5>.
Authors:
classicaltest_0.7.5.tar.gz
classicaltest_0.7.5.tar.gz(r-4.7-any)classicaltest_0.7.5.tar.gz(r-4.6-any)
classicaltest_0.7.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
classicaltest/json (API)
| # Install 'classicaltest' in R: |
| install.packages('classicaltest', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Datasets:
- dichodata - Simulated multiple choice data with 1000 cases, and 20 items
- dichokey - Keys for dichodata
- partialdata - Simulated multiple choice data with 1000 cases, and 20 items and partial credits
- partialkey - Keys for partialdata
- polydata - Simulated polytomous items data with 1000 cases, and 20 items
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:c67e156286. Checks:4 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 108 | ||
| source / vignettes | OK | 147 | ||
| linux-release-x86_64 | OK | 148 | ||
| wasm-release | OK | 80 |
Exports:alphatestclassicaltestcorrectctitemctpersonctsem.alphactsem.splitdichotomizediscriminationdistractorsitemmeanpointbiserialsplithalfstcov
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Reliability measures | alphatest splithalf |
| Classical test theory item and person statistics | classicaltest |
| Scoring correct/incorrect answers | correct |
| Classical test theory item statistics | ctitem |
| Classical test theory person statistics | ctperson |
| Standard error of measurement (SEM) | ctsem.alpha ctsem.split |
| Simulated multiple choice data with 1000 cases, and 20 items | dichodata |
| Keys for dichodata | dichokey |
| Dichotomize data | dichotomize |
| Item discrimination | discrimination |
| Distractor statistics | distractors |
| Item mean scores | itemmean |
| Simulated multiple choice data with 1000 cases, and 20 items and partial credits | partialdata |
| Keys for partialdata | partialkey |
| Point-biserial correlation | pointbiserial |
| Simulated polytomous items data with 1000 cases, and 20 items | polydata |
| Population and sample (co)variance | stcov |