This Article Full Text (PDF) All Versions of this Article: 1094428107302903v1 12/2/296    most recent References Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Alert me to new issues of the journal Add to Saved Citations Download to citation manager Request Permissions Request Reprints Add to My Marked Citations Citing Articles Citing Articles via Google Scholar Citing Articles via Scopus Google Scholar Articles by LaHuis, D. M. Articles by Copeland, D. Search for Related Content Social Bookmarking                         What's this?

Investigating Faking Using a Multilevel Logistic Regression Approach to Measuring Person Fit

Wright State University, david.lahuis{at}wright.edu

Derek Copeland

Wright State University

This article describes how a multilevel logistic regression (MLR) approach to assessing person fit can be used to test hypotheses concerning faking on personality assessments. Item difficulty and person trait estimates obtained from a two-parameter logistic item response theory model are used to predict the probability of endorsing an item in a MLR equation. The regression slope for item difficulty reflects the extent to which the probability of endorsement decreases as item difficulty increases. Less negative slopes may indicate faking, and slope variance may be modeled with person-level variables using MLR. Two examples are presented. Example 1 models faking on a personality assessment with dichotomous items. Example 2 extends the approach to scales using polytomous items.

Key Words: multilevel modeling • item response theory • response distortion

This version was published on April 1, 2009

Organizational Research Methods, Vol. 12, No. 2, 296-319 (2009)
DOI: 10.1177/1094428107302903


CiteULike    Complore    Connotea    Del.icio.us    Digg    Reddit    Technorati    Twitter    What's this?