Assessing the measurement model (MM) of self-report scales is crucial to obtain valid measurements of individuals' latent psychological constructs. This entails evaluating the number of measured constructs and determining which construct is measured by which item. Exploratory factor analysis (EFA) is the most-used method to evaluate these…

This study defines subpopulation item parameter drift (SIPD) as a change in item parameters over time that is dependent on subpopulations of examinees, and hypothesizes that the presence of SIPD in anchor items is associated with bias and/or lack of invariance in three psychometric outcomes. Results show that SIPD in anchor items is associated…

Conventional differential item functioning (DIF) detection methods (e.g., the Mantel-Haenszel test) can be used to detect DIF only across observed groups, such as gender or ethnicity. However, research has found that DIF is not typically fully explained by an observed variable. True sources of DIF may include unobserved, latent variables, such as…

This exploratory study investigated potential sources of setting accommodation resulting in differential item functioning (DIF) on math and reading assessments for examinees with varied learning characteristics. The examinees were those who participated in large-scale assessments and were tested in either standardized or accommodated testing…

The DIF-free-then-DIF (DFTD) strategy consists of two steps: (a) select a set of items that are the most likely to be DIF-free and (b) assess the other items for DIF (differential item functioning) using the designated items as anchors. The rank-based method together with the computer software IRTLRDIF can select a set of DIF-free polytomous items…

Multiple-indicators multiple-causes (MIMIC) modeling is often used to test a latent group mean difference while assuming the equivalence of factor loadings and intercepts over groups. However, this study demonstrated that MIMIC was insensitive to the presence of factor loading noninvariance, which implies that factor loading invariance should be…

There is a lack of research on the effects of outliers on the decisions about the number of factors to retain in an exploratory factor analysis, especially for outliers arising from unintended and unknowingly included subpopulations. The purpose of the present research was to investigate how outliers from an unintended and unknowingly included…

Many measurement biases affect student evaluations of instruction (SEIs). However, two have been relatively understudied: halo effects and ceiling/floor effects. This study examined these effects in two ways. To examine the halo effect, using a videotaped lecture, we manipulated specific teacher behaviors to be "good" or "bad"…

This study implements a scale purification procedure onto the standard MIMIC method for differential item functioning (DIF) detection and assesses its performance through a series of simulations. It is found that the MIMIC method with scale purification (denoted as M-SP) outperforms the standard MIMIC method (denoted as M-ST) in controlling…

This Monte Carlo study investigates the beneficiary effect of including auxiliary variables during estimation of confirmatory factor analysis models with multiple imputation. Specifically, it examines the influence of sample size, missing rates, missingness mechanism combinations, missingness types (linear or convex), and the absence or presence…

This article describes the results of a simulation study to investigate the impact of missing data on the detection of differential item functioning (DIF). Specifically, it investigates how four methods for dealing with missing data (listwise deletion, zero imputation, two-way imputation, response function imputation) interact with two methods of…

Sample-size restrictions limit the contingency table approaches based on asymptotic distributions, such as the Mantel-Haenszel (MH) procedure, for detecting differential item functioning (DIF) in many practical applications. Within this framework, the present study investigated the power and Type I error performance of empirical and inferential…

Item bias is a major threat to measurement validity. Methods for detecting differential item functioning (DIF) are now commonly used to identify potentially biased items. DIF detection methods for dichotomous items are well developed, but those for ordinal items are less well developed. In this article, the authors compare four methods for…

This study presents a procedure for detecting differential item functioning (DIF) for dichotomous and polytomous items in testlet-based tests, whereby DIF is taken into account by adding DIF parameters into the Rasch testlet model. Simulations were conducted to assess recovery of the DIF and other parameters. Two independent variables, test type…

This article compares several procedures in their efficacy for detecting differential item functioning (DIF): logistic regression analysis, the Mantel-Haenszel (MH) procedure, and the modified Mantel-Haenszel procedure by Mazor, Clauser, and Hambleton. It also compares the effect size measures that these procedures provide. In this study,…