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Greiff, Samuel; Wustenberg, Sascha; Funke, Joachim – Applied Psychological Measurement, 2012
This article addresses two unsolved measurement issues in dynamic problem solving (DPS) research: (a) unsystematic construction of DPS tests making a comparison of results obtained in different studies difficult and (b) use of time-intensive single tasks leading to severe reliability problems. To solve these issues, the MicroDYN approach is…
Descriptors: Problem Solving, Tests, Measurement, Structural Equation Models
Kahraman, Nilufer; Cuddy, Monica M.; Clauser, Brian E. – Applied Psychological Measurement, 2013
This research explores the usefulness of latent growth curve modeling in the study of pacing behavior and test speededness. Examinee response times from a high-stakes, computerized examination, collected before and after the examination was subjected to a timing change, were analyzed using a series of latent growth curve models to detect…
Descriptors: Pacing, Models, Reaction Time, Timed Tests
Culpepper, Steven Andrew – Applied Psychological Measurement, 2012
Measurement error significantly biases interaction effects and distorts researchers' inferences regarding interactive hypotheses. This article focuses on the single-indicator case and shows how to accurately estimate group slope differences by disattenuating interaction effects with errors-in-variables (EIV) regression. New analytic findings were…
Descriptors: Evidence, Test Length, Interaction, Regression (Statistics)
Levy, Roy – Applied Psychological Measurement, 2010
SEMModComp, a software package for conducting likelihood ratio tests for mean and covariance structure modeling is described. The package is written in R and freely available for download or on request.
Descriptors: Structural Equation Models, Tests, Computer Software, Models
Yang, Chongming; Nay, Sandra; Hoyle, Rick H. – Applied Psychological Measurement, 2010
Lengthy scales or testlets pose certain challenges for structural equation modeling (SEM) if all the items are included as indicators of a latent construct. Three general approaches to modeling lengthy scales in SEM (parceling, latent scoring, and shortening) have been reviewed and evaluated. A hypothetical population model is simulated containing…
Descriptors: Structural Equation Models, Measures (Individuals), Sample Size, Item Response Theory
Kim, Doyoung; De Ayala, R. J.; Ferdous, Abdullah A.; Nering, Michael L. – Applied Psychological Measurement, 2011
To realize the benefits of item response theory (IRT), one must have model-data fit. One facet of a model-data fit investigation involves assessing the tenability of the conditional item independence (CII) assumption. In this Monte Carlo study, the comparative performance of 10 indices for identifying conditional item dependence is assessed. The…
Descriptors: Item Response Theory, Monte Carlo Methods, Error of Measurement, Statistical Analysis
Hoshino, Takahiro; Shigemasu, Kazuo – Applied Psychological Measurement, 2008
The authors propose a concise formula to evaluate the standard error of the estimated latent variable score when the true values of the structural parameters are not known and must be estimated. The formula can be applied to factor scores in factor analysis or ability parameters in item response theory, without bootstrap or Markov chain Monte…
Descriptors: Monte Carlo Methods, Markov Processes, Factor Analysis, Computation
Vautier, Stephane; Bonnefon, Jean-Francois – Applied Psychological Measurement, 2008
Individuals routinely rate themselves higher than their peers on a number of attributes and capabilities, including their satisfaction with life. However, the construct validity of this above-average effect requires specific psychometric properties of ratings of one's contentment and ratings of others' perceived contentment. This article tests…
Descriptors: Life Satisfaction, Research Methodology, Construct Validity, Psychometrics
A Feedback Control Strategy for Enhancing Item Selection Efficiency in Computerized Adaptive Testing
Weissman, Alexander – Applied Psychological Measurement, 2006
A computerized adaptive test (CAT) may be modeled as a closed-loop system, where item selection is influenced by trait level ([theta]) estimation and vice versa. When discrepancies exist between an examinee's estimated and true [theta] levels, nonoptimal item selection is a likely result. Nevertheless, examinee response behavior consistent with…
Descriptors: Item Response Theory, Feedback, Adaptive Testing, Computer Assisted Testing