This package is for someone who is familiar with confirmatory factoranalysis (CFA), but not with item response theory (IRT). Although CFA isdifferently developed as opposed to IRT, both methods providemeasurement tools to validate the structure of an inventory in the scaledevelopment. However, CFA is underutilized, mainly because appliedresearchers tend not to recognize that CFA and IRT are equivalent withcertain types of indicators, such as graded response. To address thisunderutilization, this package can take and providelavaansyntax to conduct graded response model under the confirmatory factoranalysis framework.
Simulation and analysis of graded response data with different typesof estimator can be done with this package. Also, interactive shinyapplication is provided with graphics for characteristic and informationcurves.
Install the latest release from CRAN:
devtools::install_github("sooyongl/GRShiny")The documentation is available athere.
item_pars<-genIRTpar(nitem =10,ncat =3,nfac =1)true_theta<-genTheta(nsample =500,nfac =1)grm_dt<-genData(eta = true_theta,ipar = item_pars)lav_syn<-genLavSyn(dat = grm_dt,nfac =1)runGRM(dat = grm_dt,lav.syntax = lav_syn,estimator ="WL")runGRM(dat = grm_dt,lav.syntax = lav_syn,estimator ="ML")startGRshiny()