Integrative data analyses have recently been shown to be an effective tool for researchers interested in synthesizing datasets from multiple studies in order to draw statistical or substantive conclusions. The actual process of integrating the different datasets depends on the availability of some common measures or items reflecting the same…

Many education tests and psychological surveys elicit respondent views of similar constructs across scenarios (e.g., story followed by multiple choice questions) by repeating common statements across scales (one-statement-multiple-scale, OSMS). However, a respondent's earlier responses to the common statement can affect later responses to it…

In this study, the extent to wording effects impact structure and factor loadings, internal consistency and measurement invariance was outlined. The modified form, which includes items that semantically reversed, explains %21.5 more variance than the original form. Also, reversed items' factor loadings are higher. As a result of CFA, indexes…

It is common to find mixed-format data results from the use of both multiple-choice (MC) and constructed-response (CR) questions on assessments. Dealing with these mixed response types involves understanding what the assessment is measuring, and the use of suitable measurement models to estimate latent abilities. Past research in educational…

A readily and widely applicable procedure is discussed that can be used to point and interval estimate the probabilities of particular responses on polytomous items at pre-specified points along underlying latent continua. The items are assumed thereby to be part of unidimensional multi-component measuring instruments that may contain also binary…

Users of forced-choice questionnaires (FCQs) to measure personality commonly assume statement parameter invariance across contexts -- between Likert and forced-choice (FC) items and between different FC items that share a common statement. In this paper, an empirical study was designed to check these two assumptions for an FCQ assessment measuring…

Administration of patient-reported outcome measures (PROs), using multidimensional computer adaptive tests (MCATs) has the potential to reduce patient burden, but the efficiency of MCAT depends on the degree to which an individual's responses fit the psychometric properties of the assessment. Assessing patients' symptom burden through the…

In practice, some test items may display misfit at the upper-asymptote of item characteristic curve due to distraction, anxiety, or carelessness by the test takers (i.e., the slipping effect). The conventional item response theory (IRT) models do not take the slipping effect into consideration, which may violate the model fit assumption in IRT.…

This software review discusses the capabilities of Stata to conduct item response theory modeling. The commands needed for fitting the popular one-, two-, and three-parameter logistic models are initially discussed. The procedure for testing the discrimination parameter equality in the one-parameter model is then outlined. The commands for fitting…

A Monte Carlo simulation study was conducted to examine the performance of [alpha], [lambda]2, [lambda][subscript 4], [lambda][subscript 2], [omega][subscript T], GLB[subscript MRFA], and GLB[subscript Algebraic] coefficients. Population reliability, distribution shape, sample size, test length, and number of response categories were varied…

This study offers an approach to test equating under the latent D-scoring method (DSM-L) using the nonequivalent groups with anchor tests (NEAT) design. The accuracy of the test equating was examined via a simulation study under a 3 × 3 design by two conditions: group ability at three levels and test difficulty at three levels. The results for…

The property of item parameter invariance in item response theory (IRT) plays a pivotal role in the applications of IRT such as test equating. The scope of parameter invariance when using estimates from finite biased samples in the applications of IRT does not appear to be clearly documented in the IRT literature. This article provides information…

Linear logistic test models (LLTMs), leveraging item response theory and linear regression, offer an elegant method for learning about item characteristics in complex content areas. This study used LLTMs to model single-best-answer, multiple-choice-question response data from two medical subspecialty certification examinations in multiple years…

An interval estimation procedure is discussed that can be used to evaluate the probability of a particular response for a binary or binary scored item at a pre-specified point along an underlying latent continuum. The item is assumed to: (a) be part of a unidimensional multi-component measuring instrument that may contain also polytomous items,…

Multistage testing (MST), an adaptive test delivery mode that involves algorithmic selection of predefined item modules rather than individual items, offers a practical alternative to linear and fully computerized adaptive testing. However, interactions across stages between item modules and examinee groups can lead to challenges in item…