GRShiny

Overview

Simulation and analysis of graded response data with different types of estimator. Also, interactive shiny application is provided with graphics for characteristic and information curves.

Install

Install the latest release from CRAN:

devtools::install_github("sooyongl/GRShiny")

The documentation is available at here.

GRM data simulation

Item parameters for graded response model

item_pars <- genIRTpar(nitem = 10, ncat = 3, nfac = 1)

Individual true latent traits

true_theta <- genTheta(nsample = 500, nfac = 1)

GRM data

grm_dt <- genData(eta = true_theta, ipar = item_pars)

GRM data simulation

Generate lavaan syntax

lav_syn <- genLavSyn(dat = grm_dt, nfac = 1)

Conduct GRM with two different estimators

runGRM(dat = grm_dt, lav.syntax = lav_syn, estimator = "WL")

runGRM(dat = grm_dt, lav.syntax = lav_syn, estimator = "ML")

Launch app

startGRshiny()