This package is considered a duplicate. The official version of this package is found at:https://naidantu.r-universe.dev/fcirt

Package: fcirt 0.2.1

Naidan Tu

fcirt: Forced Choice in Item Response Theory

Bayesian estimation of forced choice models in Item Response Theory using 'rstan' (See Stan Development Team (2020) <https://mc-stan.org/>).

Authors:Naidan Tu [aut, cre], Seang-Hwane Joo [aut], Philseok Lee [aut], Stephen Stark [aut]

fcirt_0.2.1.tar.gz
fcirt_0.2.1.zip(r-4.7-x86_64)fcirt_0.2.1.zip(r-4.7-arm64)fcirt_0.2.1.zip(r-4.6-x86_64)fcirt_0.2.1.zip(r-4.6-arm64)
fcirt_0.2.1.tar.gz(r-4.7-arm64)fcirt_0.2.1.tar.gz(r-4.7-x86_64)fcirt_0.2.1.tar.gz(r-4.6-arm64)fcirt_0.2.1.tar.gz(r-4.6-x86_64)
fcirt_0.2.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
fcirt/json (API)

# Install 'fcirt' in R:

install.packages('fcirt', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/naidantu/fcirt/issues

Uses libs:

onetbb– Parallelism library for C++
c++– GNU Standard C++ Library v3

On CRAN:

2.70 score 7 scripts 258 downloads 4 exports 49 dependencies

Last updated from:7ea3ef5376. Checks:8 WARNING, 2 OK. Indexed: no.

Target	Result	Time	Files	Syslog
linux-devel-arm64	WARNING	209
linux-devel-x86_64	WARNING	236
source / vignettes	OK	277
linux-release-arm64	WARNING	198
linux-release-x86_64	WARNING	234
windows-devel-arm64	WARNING	357
windows-devel-x86_64	WARNING	294
windows-release-arm64	WARNING	315
windows-release-x86_64	WARNING	258
wasm-release	OK	194

Exports:bayesplot extract fcirt information

Dependencies:abind backports BH callr checkmate cli cpp11 desc distributional edstan farver generics ggplot2 glue gridExtra gtable inline isoband labeling lifecycle loo magrittr matrixStats numDeriv otel pillar pkgbuild pkgconfig posterior processx ps QuickJSR R6 RColorBrewer Rcpp RcppEigen RcppParallel rlang rstan rstantools S7 scales StanHeaders tensorA tibble utf8 vctrs viridisLite withr

fcirt: Forced Choice in Item Response Theory

Overview | Tutorial | Step 1: Input data | Step 2: Estimate using the function fcirt() | Step 3: Extract the estimated results using the function extract() | Step 4: Plotting using the function bayesplot() | Step 5: Obtain item and item information using the function information()

Rendered frommy-vignette.Rmdusingknitr::rmarkdown

Last update: 2025-08-19
Started: 2022-02-01

Citation

Readme and manuals

Help Manual

Help page	Topics
bayesian convergence diagnosis plotting function	bayesplot
results extraction	extract
forced choice model estimation	fcirt
mfc item and test information	information

Usage by other packages (reverse dependencies)