Package: GRShiny 1.0.1

Sooyong Lee

GRShiny: Graded Response Model

Simulation and analysis of graded response data with different types of estimators. Also, an interactive shiny application is provided with graphics for characteristic and information curves. Samejima (2018) <doi:10.1007/978-1-4757-2691-6_5>.

Authors:Sooyong Lee [aut, cre], Tiffany Whittaker [aut], Laura Stapleton [aut]

GRShiny_1.0.1.tar.gz
GRShiny_1.0.1.zip(r-4.7)GRShiny_1.0.1.zip(r-4.6)GRShiny_1.0.1.zip(r-4.5)
GRShiny_1.0.1.tgz(r-4.6-any)GRShiny_1.0.1.tgz(r-4.5-any)
GRShiny_1.0.1.tar.gz(r-4.7-any)GRShiny_1.0.1.tar.gz(r-4.6-any)
GRShiny_1.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
GRShiny/json (API)

# Install 'GRShiny' in R:

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

Bug tracker:https://github.com/sooyongl/grshiny/issues

On CRAN:

4.00 score 10 scripts 506 downloads 12 exports 163 dependencies

Last updated from:902a56e4c5. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	235
source / vignettes	OK	329
linux-release-x86_64	OK	241
macos-release-arm64	OK	207
macos-oldrel-arm64	OK	274
windows-devel	OK	186
windows-release	OK	154
windows-oldrel	OK	179
wasm-release	OK	150

Exports:ESplot extract_est extract_fit FSplot genData genIRTpar genLavSyn genTheta ICCplot infoPlot runGRM startGRshiny

Dependencies:admisc askpass audio base64enc beepr bigD bit bit64 bitops brio bslib cachem callr CDM class cli clipr cluster codetools commonmark cpp11 crayon crosstalk curl data.table dcurver Deriv desc diffobj digest dplyr DT e1071 evaluate farver fastmap flextable fontawesome fontBitstreamVera fontLiberation fontquiver fs future future.apply gdtools generics ggplot2 globals glue GPArotation gridExtra gt gtable highr hms htmltools htmlwidgets httpuv isoband jquerylib jsonlite juicyjuice knitr labeling later lattice lavaan lazyeval lifecycle listenv litedown magrittr markdown MASS Matrix memoise mgcv mime mirai mirt mnormt mvtnorm nanonext nlme numDeriv officer openssl openxlsx otel parallelly pbapply pbivnorm pbv permute pillar pkgbuild pkgconfig pkgload polycor praise prettyunits processx progress progressr promises proxy ps purrr qs2 quadprog R.methodsS3 R.oo R.utils R6 ragg rappdirs RColorBrewer Rcpp RcppArmadillo RcppParallel reactable reactR readr rlang rmarkdown rprojroot S7 sass scales sessioninfo shiny shinyWidgets SimDesign sirt sourcetools splines2 stringfish stringi stringr sys systemfonts TAM testthat textshaping tibble tidyr tidyselect tinytex tzdb utf8 uuid V8 vctrs vegan viridisLite vroom waldo withr xfun xml2 xtable yaml zip

GRShiny

Rendered fromGRShiny.Rmdusingknitr::rmarkdown

Last update: 2023-05-04
Started: 2022-01-26

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Full information maximum likelihood estimation of IRT models.	GRShiny-package GRShiny
Plot expected scores by items	ESplot
Clean output to look like Mplus	extract_est
Extract model fit	extract_fit
Plot Factor score	FSplot
Generate IRT data	genData
Generate Item parameters	genIRTpar
Generate lavaan syntax	genLavSyn
Generate individual true latent traits	genTheta
Plot ICC or OCC	ICCplot
Calculate item information	infoPlot
Run graded response model	runGRM
Start GRShiny	startGRshiny