RMSEA Item Fit Statistics for TAM Objects

Description

Computes the RMSEA item fit statistic for fitted objects in the TAM package, see CDM::IRT.itemfit and CDM::itemfit.rmsea.

Usage

## S3 method for class 'tam.mml'
IRT.itemfit(object, method="rmsea", ...)

## S3 method for class 'tam.mml.2pl'
IRT.itemfit(object, method="rmsea", ...)

## S3 method for class 'tam.mml.mfr'
IRT.itemfit(object, method="rmsea", ...)

## S3 method for class 'tam.mml.3pl'
IRT.itemfit(object, method="rmsea", ...)

Arguments

See Also

CDM::IRT.itemfit, CDM::itemfit.rmsea

Examples

## Not run: 
#############################################################################
# EXAMPLE 1: RMSEA item fit statistic data.read
#############################################################################

library(sirt)
data(data.read,package="sirt")
dat <- data.read

#*** fit 1PL model
mod1 <- tam.mml( dat )
summary(mod1)

#*** fit 2PL model
mod2 <- tam.mml.2pl( dat )
summary(mod2)

#*** assess RMSEA item fit
fmod1 <- IRT.itemfit(mod1)
fmod2 <- IRT.itemfit(mod2)
# summary of fit statistics
summary( fmod1$rmsea )
summary( fmod2$rmsea )

#############################################################################
# SIMULATED EXAMPLE 2: Simulated 2PL data and fit of 1PL model
#############################################################################

set.seed(987)
N <- 1000    # 1000 persons
I <- 10      # 10 items
# define item difficulties and item slopes
b <- seq(-2,2,len=I)
a <- rep(1,I)
a[c(3,8)] <- c( 1.7 , .4 )
# simulate 2PL data
dat <- sirt::sim.raschtype( theta=rnorm(N) , b = b , fixed.a = a)

# fit 1PL model
mod <- tam.mml( dat )

# RMSEA item fit
fmod <- IRT.itemfit(mod)
round( fmod$rmsea , 3 )

## End(Not run)

Results