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de la Torre, Jimmy; Song, Hao; Hong, Yuan – Applied Psychological Measurement, 2011
Lack of sufficient reliability is the primary impediment for generating and reporting subtest scores. Several current methods of subscore estimation do so either by incorporating the correlational structure among the subtest abilities or by using the examinee's performance on the overall test. This article conducted a systematic comparison of four…
Descriptors: Item Response Theory, Scoring, Methods, Comparative Analysis
Finkelman, Matthew D.; Smits, Niels; Kim, Wonsuk; Riley, Barth – Applied Psychological Measurement, 2012
The Center for Epidemiologic Studies-Depression (CES-D) scale is a well-known self-report instrument that is used to measure depressive symptomatology. Respondents who take the full-length version of the CES-D are administered a total of 20 items. This article investigates the use of curtailment and stochastic curtailment (SC), two sequential…
Descriptors: Measures (Individuals), Depression (Psychology), Test Length, Computer Assisted Testing
Nandakumar, Ratna; Yu, Feng; Zhang, Yanwei – Applied Psychological Measurement, 2011
DETECT is a nonparametric methodology to identify the dimensional structure underlying test data. The associated DETECT index, "D[subscript max]," denotes the degree of multidimensionality in data. Conditional covariances (CCOV) are the building blocks of this index. In specifying population CCOVs, the latent test composite [theta][subscript TT]…
Descriptors: Nonparametric Statistics, Statistical Analysis, Tests, Data
Kieftenbeld, Vincent; Natesan, Prathiba – Applied Psychological Measurement, 2012
Markov chain Monte Carlo (MCMC) methods enable a fully Bayesian approach to parameter estimation of item response models. In this simulation study, the authors compared the recovery of graded response model parameters using marginal maximum likelihood (MML) and Gibbs sampling (MCMC) under various latent trait distributions, test lengths, and…
Descriptors: Test Length, Markov Processes, Item Response Theory, Monte Carlo Methods
Cui, Zhongmin; Kolen, Michael J. – Applied Psychological Measurement, 2008
This article considers two methods of estimating standard errors of equipercentile equating: the parametric bootstrap method and the nonparametric bootstrap method. Using a simulation study, these two methods are compared under three sample sizes (300, 1,000, and 3,000), for two test content areas (the Iowa Tests of Basic Skills Maps and Diagrams…
Descriptors: Test Length, Test Content, Simulation, Computation
Woods, Carol M. – Applied Psychological Measurement, 2007
Ramsay curve item response theory (RC-IRT) was recently developed to detect and correct for nonnormal latent variables when unidimensional IRT models are fitted to data using maximum marginal likelihood estimation. The purpose of this research is to evaluate the performance of RC-IRT for Likert-type item responses with varying test lengths, sample…
Descriptors: Test Length, Item Response Theory, Sample Size, Comparative Analysis
Peer reviewedStark, Stephen; Drasgow, Fritz – Applied Psychological Measurement, 2002
Describes item response and information functions for the Zinnes and Griggs paired comparison item response theory (IRT) model (1974) and presents procedures for estimating stimulus and person parameters. Monte Carlo simulations show that at least 400 ratings are required to obtain reasonably accurate estimates of the stimulus parameters and their…
Descriptors: Comparative Analysis, Computer Simulation, Error of Measurement, Item Response Theory
Peer reviewedNoonan, Brian W.; And Others – Applied Psychological Measurement, 1992
Studied the extent to which three appropriateness indexes, Z(sub 3), ECIZ4, and W, are well standardized in a Monte Carlo study. The ECIZ4 most closely approximated a normal distribution, and its skewness and kurtosis were more stable and less affected by test length and item response theory model than the others. (SLD)
Descriptors: Comparative Analysis, Item Response Theory, Mathematical Models, Maximum Likelihood Statistics

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