Package: RSP 0.4

Eren Can Aybek

RSP: 'shiny' Applications for Statistical and Psychometric Analysis

Toolbox with 'shiny' applications for widely used psychometric methods. Those methods include following analysis: Item analysis, item response theory calibration, principal component analysis, confirmatory factor analysis - structural equation modeling, generating simulated data. References: Chalmers (2012, <doi:10.18637/jss.v048.i06>); Revelle (2022, <https://CRAN.R-project.org/package=psych Version = 2.2.9.>); Rosseel (2012, <doi:10.18637/jss.v048.i02>); Magis & Raiche (2012, <doi:10.18637/jss.v048.i08>); Magis & Barrada (2017, <doi:10.18637/jss.v076.c01>).

Authors:Celal Deha Dogan [aut], Eren Can Aybek [aut, cre], Sumeyra Soysal [ctb]

RSP_0.4.tar.gz
RSP_0.4.tar.gz(r-4.5-noble)RSP_0.4.tar.gz(r-4.4-noble)
RSP_0.4.tgz(r-4.4-emscripten)RSP_0.4.tgz(r-4.3-emscripten)
RSP.pdf |RSP.html✨
RSP/json (API)

# Install 'RSP' in R:

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

Uses libs:

openjdk– OpenJDK Java runtime, using Hotspot JIT

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.26 score 18 scripts 205 downloads 7 exports 206 dependencies

Last updated 1 years agofrom:70456c1205. Checks:OK: 2. Indexed: no.

Target	Result	Date
Doc / Vignettes	OK	Oct 18 2024
R-4.5-linux	OK	Oct 18 2024

Exports:CFA FA INTERNAL IRT ITEMAN PCA SIMDATA

Dependencies:abind admisc arm audio backports base64enc beepr BH bigD bitops boot brio broom bslib cachem callr car carData catR checkmate cli cluster coda codetools colorspace commonmark corpcor cowplot cpp11 crayon crosstalk curl data.table dcurver deltaPlotR Deriv desc diffobj difR digest doBy dplyr DT energy evaluate expm fansi farver fastmap fdrtool fontawesome foreign Formula fs future future.apply generics ggplot2 glasso globals glue GPArotation gridExtra gsl gt gtable gtools highr Hmisc hornpa htmlTable htmltools htmlwidgets httpuv igraph isoband jpeg jquerylib jsonlite juicyjuice knitr kutils labeling later lattice lavaan lazyeval lifecycle lisrelToR listenv lme4 ltm magrittr markdown MASS Matrix MatrixModels memoise Metrics mgcv mi microbenchmark mime minqa mirt mnormt modelr moments msm munsell MVN mvtnorm nlme nloptr nnet nortest numDeriv OpenMx openxlsx parallelly pbapply pbivnorm pbkrtest permute pillar pkgbuild pkgconfig pkgload plyr png polycor praise processx progressr promises ps psych purrr qgraph quadprog quantreg R.methodsS3 R.oo R.utils R6 rappdirs RColorBrewer Rcpp RcppArmadillo RcppEigen RcppParallel reactable reactR rematch2 reshape2 rJava rlang rmarkdown rockchalk rpart rpf rprojroot RPushbullet rstudioapi RUnit sass scales sem semPlot sessioninfo shiny shinyBS shinycustomloader ShinyItemAnalysis shinyjs shinythemes shinyWidgets SimDesign snow sourcetools SparseM StanHeaders stringi stringr survival testthat tibble tidyr tidyselect tinytex utf8 V8 vctrs vegan viridis viridisLite waldo withr xfun xlsx xlsxjars XML xml2 xtable yaml zip

Introduction to RSP Package

Rendered fromINTRO_RSP.Rmdusingknitr::rmarkdownon Oct 18 2024.

Last update: 2023-01-17
Started: 2023-01-17

Help page	Topics
Testing measurement & structural models for dichotomous and polytomous data	CFA
Run exploratory factor analysis for dichotomous and polytomous data	FA
Run exploratory factor analysis for dichotomous and polytomous data	INTERNAL
Item calibration according to item response theory models	IRT
Item and test statistics based on classical test theory,	ITEMAN
Run principal component analysis for dichotomous and polytomous data	PCA
Generate simulated data according to IRT for dichotomous and polytomous data Generate multidimensional data for factor analysis # param options(java.parameters = "-Xmx8000m")	SIMDATA

Package: RSP 0.4

RSP: 'shiny' Applications for Statistical and Psychometric Analysis

Introduction to RSP Package

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)