itemPar3PLconst {difR}R Documentation

Item parameter estimation for DIF detection using constrained 3PL model

Description

Fits the 3PL model with constrained pseudo-guessing values and returns related item parameter estimates.

Usage

 itemPar3PLconst(data, c=rep(0,ncol(data)))

Arguments

data numeric: the data matrix.
c numeric value or vector of constrained pseudo-guessing parameters. See Details.

Details

itemPar3PLconst permits to get item parameter estimates from the 3PL model for which the pseudo-guessing parameters are constrained to some fixed values. The output is ordered such that it can be directly used with the general itemParEst command, as well as the methods of Lord (difLord) and Raju (difRaju) and Generalized Lord's (difGenLord) to detect differential item functioning.

The output is similar to that of itemPar2PL method to fit the 2PL model; an additional column is included and holds the fixed pseudo-guessing parameter values.

The data is a matrix whose rows correspond to the subjects and columns to the items. Missing values are not allowed.

The argument c can be either a single numeric value or a numeric vector of the same length of the number of items. In the former case, the pseudo-guessing parameters are considered to be all identical to the given c value; otherwise c is directly used to constraint these parameters.

The constrained 3PL model is fitted using marginal maximum likelihood by means of the functions from the ltm package (Rizopoulos, 2006).

Value

A matrix with one row per item and six columns: the item discrimination a and difficulty estimates b, the corresponding standard errors se(a) and se(b), the covariances cov(a,b)and the constrained pseudo-guessing values c.

Author(s)

Sebastien Beland
Centre sur les Applications des Modeles de Reponses aux Items (CAMRI)
Universite du Quebec a Montreal
sebastien.beland.1@hotmail.com
David Magis
Research Group of Quantitative Psychology and Individual Differences
Katholieke Universiteit Leuven
David.Magis@psy.kuleuven.be, http://ppw.kuleuven.be/okp/home/
Gilles Raiche
Centre sur les Applications des Modeles de Reponses aux Items (CAMRI)
Universite du Quebec a Montreal
raiche.gilles@uqam.ca, http://www.er.uqam.ca/nobel/r17165/

References

Rizopoulos, D. (2006). ltm: An R package for latent variable modelling and item response theory analyses. Journal of Statistical Software, 17, 1-25. URL: http://www.jstatsoft.org/v17/i05/

See Also

itemPar1PL, itemPar2PL, itemPar3PL, itemParEst, difLord, difRaju, difGenLord

Examples

# Loading of the verbal data
data(verbal)

# Constraining all pseudo-guessing parameters to be equal to 0.05
itemPar3PLconst(verbal[,1:24], c=0.05)

# Constraining pseudo-guessing values to  0.1 for the first 10 items, 
# and to 0.05 for the remaining ones
itemPar3PLconst(verbal[,1:24], c=c(rep(0.1,10),rep(0.05,14)))

[Package difR version 1.1 Index]