immer (version 0.4-0)

immer_opcat: Estimation of Integer Item Discriminations

Description

Estimates integer item discrminations like in the one-parameter logistic model (OPLM; Verhelst & Glas, 1995). See Verhelst, Verstralen and Eggen (1991) for computational details.

Usage

immer_opcat(a, hmean, min = 1, max = 10, maxiter = 200)

Arguments

a

Vector of estimated item discriminations

hmean

Prespecified harmonic mean

min

Minimum integer item discrmination

max

Maximum integer item discrimination

maxiter

Maximum number of iterations

Value

• Vector containing integer item discriminations

References

Verhelst, N. D. &, Glas, C. A. W. (1995). The one-parameter logistic model. In G. H. Fischer & I. W. Molenaar (Eds.). Rasch Models (pp. 215--238). New York: Springer. Verhelst, N. D., Verstralen, H. H. F. M., & Eggen, T. H. J. M. (1991). Finding starting values for the item parameters and suitable discrimination indices in the one-parameter logistic model. CITO Measurement and Research Department Reports, 91-10.

See Also

See immer_cml for using immer_opcat to estimate the one-parameter logistic model.

Examples

#############################################################################
# EXAMPLE 1: Estimating integer item discriminations for dichotomous data
#############################################################################

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

#--- estimate 2PL model
mod <- sirt::rasch.mml2( dat , est.a = 1:I  , mmliter= 30)
summary(mod)
a <- mod$item$a		# extract (non-integer) item discriminations 

#--- estimate integer item discriminations under different conditions
a1 <- immer_opcat( a , hmean = 3 , min = 1 , max = 6 )
table(a1)
a2 <- immer_opcat( a , hmean = 2 , min = 1 , max = 3 )
a3 <- immer_opcat( a , hmean = 1.5 , min = 1 , max = 2 )
#--- compare results
cbind( a , a1 , a2 , a3)