Item purification is an iterative process that is often advocated as improving the identification of items affected by differential item functioning (DIF). With test-score-based DIF detection methods, item purification iteratively removes the items currently flagged as DIF from the test scores to get purified sets of items, unaffected by DIF. The…

Differential item functioning (DIF) occurs when the probability of responding in a particular category to an item differs for members of different groups who are matched on the construct being measured. The identification of DIF is important for valid measurement. This research evaluates an improved version of Lord's X[superscript 2] Wald test for…

In a typical differential item functioning (DIF) analysis, a significance test is conducted for each item. As a test consists of multiple items, such multiple testing may increase the possibility of making a Type I error at least once. The goal of this study was to investigate how to control a Type I error rate and power using adjustment…

Local dependence (LD) for binary IRT models can be diagnosed using Chen and Thissen's bivariate X[superscript 2] statistic and the score test statistics proposed by Glas and Suarez-Falcon, and Liu and Thissen. Alternatively, LD can be assessed using general purpose statistics such as bivariate residuals or Maydeu-Olivares and Joe's M[subscript r]…

Traditional estimators of item response theory scale scores ignore uncertainty carried over from the item calibration process, which can lead to incorrect estimates of the standard errors of measurement (SEMs). Here, the authors review a variety of approaches that have been applied to this problem and compare them on the basis of their statistical…

The identification of differential item functioning (DIF) is often performed by means of statistical approaches that consider the raw scores as proxies for the ability trait level. One of the most popular approaches, the Mantel-Haenszel (MH) method, belongs to this category. However, replacing the ability level by the simple raw score is a source…

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…

Issues with correlation attenuation due to measurement error are well documented. More than a century ago, Spearman proposed a correction for attenuation. However, this correction has seen very little use since it can potentially inflate the true correlation beyond one. In addition, very little confidence interval (CI) research has been done for…

In 2009, DeMars stated that when impact exists there will be Type I error inflation, especially with larger sample sizes and larger discrimination parameters for items. One purpose of this study is to present the patterns of Type I error rates using Mantel-Haenszel (MH) and logistic regression (LR) procedures when the mean ability between the…

Though much research and attention has been directed at assessing the correlation coefficient under range restriction, the assessment of reliability under range restriction has been largely ignored. This article uses item response theory to simulate dichotomous item-level data to assess the robustness of KR-20 ([alpha]), [omega], and test-retest…

A latent variable modeling approach that permits estimation of propensity scores in observational studies containing fallible independent variables is outlined, with subsequent examination of treatment effect. When at least one covariate is measured with error, it is indicated that the conventional propensity score need not possess the desirable…

This study used Monte Carlo simulation to examine the properties of the overall odds ratio (OOR), which was recently introduced as an index for overall effect size in multiple logistic regression. It was found that the OOR was relatively independent of study base rate and performed better than most commonly used R-square analogs in indexing model…

The generalized binomial test (GBT) and [omega] indices are the most recent methods suggested in the literature to detect answer copying behavior on multiple-choice tests. The [omega] index is one of the most studied indices, but there has not yet been a systematic simulation study for the GBT index. In addition, the effect of the ability levels…

Missing information is a ubiquitous aspect of data analysis, including responses to items on cognitive and affective instruments. Although the broader statistical literature describes missing data methods, relatively little work has focused on this issue in the context of differential item functioning (DIF) detection. Such prior research has…

There is a long history of differential item functioning (DIF) detection methods for known, manifest grouping variables, such as sex or ethnicity. But if the experiences or cognitive processes leading to DIF are not perfectly correlated with the manifest groups, it would be more informative to uncover the latent groups underlying DIF. The use of…