Package: GRShiny 1.0.0

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_1.0.0.tar.gz
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GRShiny.pdf |GRShiny.html✨
GRShiny/json (API)
NEWS

# 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:

3.70 score 3 scripts 218 downloads 12 exports 157 dependencies

Last updated 2 years agofrom:174d357edb. Checks:OK: 3 NOTE: 4. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Oct 25 2024
R-4.5-win	NOTE	Oct 25 2024
R-4.5-linux	NOTE	Oct 25 2024
R-4.4-win	NOTE	Oct 25 2024
R-4.4-mac	NOTE	Oct 25 2024
R-4.3-win	OK	Oct 25 2024
R-4.3-mac	OK	Oct 25 2024

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 cli clipr cluster codetools colorspace commonmark cpp11 crayon crosstalk curl data.table dcurver Deriv desc diffobj digest dplyr DT evaluate fansi 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 magrittr markdown MASS Matrix memoise mgcv mime mirt mnormt munsell mvtnorm nlme numDeriv officer openssl openxlsx parallelly pbapply pbivnorm pbv permute pillar pkgbuild pkgconfig pkgload polycor praise prettyunits processx progress progressr promises ps purrr quadprog R.methodsS3 R.oo R.utils R6 ragg rappdirs RColorBrewer Rcpp RcppArmadillo reactable reactR readr rematch2 rlang rmarkdown rprojroot RPushbullet sass scales sessioninfo shiny shinyWidgets SimDesign sirt snow sourcetools 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::rmarkdownon Oct 25 2024.

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
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