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Hoofs, Huub; van de Schoot, Rens; Jansen, Nicole W. H.; Kant, IJmert – Educational and Psychological Measurement, 2018
Bayesian confirmatory factor analysis (CFA) offers an alternative to frequentist CFA based on, for example, maximum likelihood estimation for the assessment of reliability and validity of educational and psychological measures. For increasing sample sizes, however, the applicability of current fit statistics evaluating model fit within Bayesian…
Descriptors: Goodness of Fit, Bayesian Statistics, Factor Analysis, Sample Size
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Woods, Carol M. – Applied Psychological Measurement, 2011
Differential item functioning (DIF) occurs when an item on a test, questionnaire, or interview has different measurement properties for one group of people versus another, irrespective of true group-mean differences on the constructs being measured. This article is focused on item response theory based likelihood ratio testing for DIF (IRT-LR or…
Descriptors: Simulation, Item Response Theory, Testing, Questionnaires
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Bernaards, Coen A.; Sijtsma, Klaas – Multivariate Behavioral Research, 2000
Using simulation, studied the influence of each of 12 imputation methods and 2 methods using the EM algorithm on the results of maximum likelihood factor analysis as compared with results from the complete data factor analysis (no missing scores). Discusses why EM methods recovered complete data factor loadings better than imputation methods. (SLD)
Descriptors: Factor Analysis, Maximum Likelihood Statistics, Questionnaires, Simulation
Tsutakawa, Robert K. – 1983
This paper presents a method for estimating certain characteristics of test items which are designed to measure ability, or knowledge, in a particular area. Under the assumption that ability parameters are sampled from a normal distribution, the EM algorithm is used to derive maximum likelihood estimates to item parameters of the two-parameter…
Descriptors: Attitude Measures, Estimation (Mathematics), Latent Trait Theory, Maximum Likelihood Statistics