The interpretation of psychometric test results is usually based on norm scores. We compared semiparametric continuous norming (SPCN) with conventional norming methods by simulating results for test scales with different item numbers and difficulties via an item response theory approach. Subsequently, we modeled the norm scores based on random…

This study presents new models for item response functions (IRFs) in the framework of the D-scoring method (DSM) that is gaining attention in the field of educational and psychological measurement and largescale assessments. In a previous work on DSM, the IRFs of binary items were estimated using a logistic regression model (LRM). However, the LRM…

An approach to scoring tests with binary items, referred to as D-scoring method, was previously developed as a classical analog to basic models in item response theory (IRT) for binary items. As some tests include polytomous items, this study offers an approach to D-scoring of such items and parallels the results with those obtained under the…

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…

The purpose of this article is to highlight the distinction between the reliability of test scores and the fit of psychometric measurement models, reminding readers why it is important to consider both when evaluating whether test scores are valid for a proposed interpretation and/or use. It is often the case that an investigator judges both the…

The purpose of the present studies was to test the hypothesis that the psychometric characteristics of ability scales may be significantly distorted if one accounts for emotional factors during test taking. Specifically, the present studies evaluate the effects of anxiety and motivation on the item difficulties of the Rasch model. In Study 1, the…

When conducting item reviews, analysts evaluate an array of statistical and graphical information to assess the fit of a field test (FT) item to an item response theory model. The process can be tedious, particularly when the number of human reviews (HR) to be completed is large. Furthermore, such a process leads to decisions that are susceptible…

This study compared the functioning of positively and negatively worded personality items using item response theory. In Study 1, word pairs from the Goldberg Adjective Checklist were analyzed using the Graded Response Model. Across subscales, negatively worded items produced comparatively higher difficulty and lower discrimination parameters than…

In recent studies, different methods were proposed to investigate invariant item ordering (IIO), but practical IIO research is an unexploited field in questionnaire construction and evaluation. In the present study, the authors explored the usefulness of different IIO methods to analyze personality scales and clinical scales. From the authors'…

Recent research suggests that competitive work environments may influence individual's attitudes, behaviors, stress, and performance. Unfortunately, adequate measures of competitive environments are lacking. This article traces the development of a new multidimensional competitive work environment scale. An initial 59-item pool covering five…

A common question in test evaluation is whether an a priori assignment of items to subtests is supported by empirical data. If the analysis results indicate the assignment of items to subtests under study is not supported by data, the assignment is often adjusted. In this study the authors compare two methods on the quality of their suggestions to…

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…

The linear logistic test model (LLTM) breaks down the item parameter of the Rasch model as a linear combination of some hypothesized elementary parameters. Although the original purpose of applying the LLTM was primarily to generate test items with specified item difficulty, there are still many other potential applications, which may be of use…

In this study, mixed Rasch modeling was used on the Self-Rating Depression Scale (SDS), a widely used measure of depression, among a non-Western sample of 618 Korean college students. The results revealed three latent classes and confirmed the unidimensionality of the SDS. In addition, there was a significant effect for gender in terms of class…

This study compared four methods for setting item response time thresholds to differentiate rapid-guessing behavior from solution behavior. Thresholds were either (a) common for all test items, (b) based on item surface features such as the amount of reading required, (c) based on visually inspecting response time frequency distributions, or (d)…