Applied Psychological Measurement

Han, Kyung (Chris) T.

doi: 10.1177/0146621619837226pmid: 32076354

Multistage testing (MST) has many practical advantages over typical item-level computerized adaptive testing (CAT), but there is a substantial tradeoff when using MST because of its reduced level of adaptability. In typical MST, the first stage almost always performs as a routing stage in which all test takers see a linear test form. If multiple test sections measure different but moderately or highly correlated traits, then a score estimate for one section might be capable of adaptively selecting item modules for following sections without having to administer routing stages repeatedly for each section. In this article, a new framework for developing MST with intersectional routing (ISR) was proposed and evaluated under several research conditions with different MST structures, section score distributions and relationships, and types of regression models for ISR. The overall findings of the study suggested that MST with ISR approach could improve measurement efficiency and test optimality especially with tests with short lengths.

Debelak, Rudolf; Koller, Ingrid

doi: 10.1177/0146621619835501pmid: 32076355

Local independence is a central assumption of commonly used item response theory models. Violations of this assumption are usually tested using test statistics based on item pairs. This study presents two quasi-exact tests based on the Q3 statistic for testing the hypothesis of local independence in the Rasch model. The proposed tests do not require the estimation of item parameters and can also be applied to small data sets. The authors evaluate the tests with three simulation studies. Their results indicate that the quasi-exact tests hold their alpha level under the Rasch model and have higher power against different forms of local dependence than several alternative parametric and nonparametric model tests for local independence.

Montoya, Amanda K.; Jeon, Minjeong

doi: 10.1177/0146621619835496pmid: 32076356

In this article, the authors describe how multiple indicators multiple cause (MIMIC) models for studying uniform and nonuniform differential item functioning (DIF) can be conceptualized as mediation and moderated mediation models. Conceptualizing DIF within the context of a moderated mediation model helps to understand DIF as the effect of some variable on measurements that is not accounted for by the latent variable of interest. In addition, useful concepts and ideas from the mediation and moderation literature can be applied to DIF analysis: (a) improving the understanding of uniform and nonuniform DIF as direct effects and interactions, (b) understanding the implication of indirect effects in DIF analysis, (c) clarifying the interpretation of the “uniform DIF parameter” in the presence of nonuniform DIF, and (d) probing interactions and using the concept of “conditional effects” to better understand the patterns of DIF across the range of the latent variable.

Kim, Seohyun; Lu, Zhenqiu; Cohen, Allan S.

doi: 10.1177/0146621619835498pmid: 32076357

This study describes a structural equation modeling (SEM) approach to reliability for tests with items having different numbers of ordered categories. A simulation study is provided to compare the performance of this reliability coefficient, coefficient alpha and population reliability for tests having items with different numbers of ordered categories, a one-factor and a bifactor structures, and different skewness distributions of test scores. Results indicated that the proposed reliability coefficient was close to the population reliability in most conditions. An empirical example was used to illustrate the performance of the different coefficients for a test of items with two or three ordered categories.

Sen, Sedat; Terzi, Ragip

doi: 10.1177/0146621619843822pmid: N/A

This article provides a review of software packages for fitting maximum likelihood estimation of the deterministic input, noisy “and” gate (DINA) model. Six software packages—flexMIRT, Latent GOLD, mdltm, Mplus, OxEdit, and R—are considered. Each package is reviewed regarding data manipulation, statistical capabilities, output, and documentation. The results of these packages are compared using a sample data set and a Q-matrix. The article aims to give the reader a summary of the different capabilities of each package.