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When Can Categorical Variables Be Treated as Continuous? A Comparison of Robust Continuous and Categorical SEM Estimation Methods under Suboptimal Conditions
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Rhemtulla, Mijke; Brosseau-Liard, Patricia E.; Savalei, Victoria – Psychological Methods, 2012
A simulation study compared the performance of robust normal theory maximum likelihood (ML) and robust categorical least squares (cat-LS) methodology for estimating confirmatory factor analysis models with ordinal variables. Data were generated from 2 models with 2-7 categories, 4 sample sizes, 2 latent distributions, and 5 patterns of category…
Descriptors: Factor Analysis, Computation, Simulation, Sample Size
A Model-Averaging Approach to Replication : The Case of "p[subscript rep]"
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Iverson, Geoffrey J.; Wagenmakers, Eric-Jan; Lee, Michael D. – Psychological Methods, 2010
The purpose of the recently proposed "p[subscript rep]" statistic is to estimate the probability of concurrence, that is, the probability that a replicate experiment yields an effect of the same sign (Killeen, 2005a). The influential journal "Psychological Science" endorses "p[subscript rep]" and recommends its use…
Descriptors: Effect Size, Evaluation Methods, Probability, Experiments
Estimation of IRT Graded Response Models: Limited versus Full Information Methods
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Forero, Carlos G.; Maydeu-Olivares, Alberto – Psychological Methods, 2009
The performance of parameter estimates and standard errors in estimating F. Samejima's graded response model was examined across 324 conditions. Full information maximum likelihood (FIML) was compared with a 3-stage estimator for categorical item factor analysis (CIFA) when the unweighted least squares method was used in CIFA's third stage. CIFA…
Descriptors: Factor Analysis, Least Squares Statistics, Computation, Item Response Theory
Conceptualizing and Testing Random Indirect Effects and Moderated Mediation in Multilevel Models: New Procedures and Recommendations
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Bauer, Daniel J.; Preacher, Kristopher J.; Gil, Karen M. – Psychological Methods, 2006
The authors propose new procedures for evaluating direct, indirect, and total effects in multilevel models when all relevant variables are measured at Level 1 and all effects are random. Formulas are provided for the mean and variance of the indirect and total effects and for the sampling variances of the average indirect and total effects.…
Descriptors: Testing, Models, Sampling, Context Effect
Inequality Constrained Analysis of Variance: A Bayesian Approach
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Klugkist, Irene; Laudy, Olav; Hoijtink, Herbert – Psychological Methods, 2005
Researchers often have one or more theories or expectations with respect to the outcome of their empirical research. When researchers talk about the expected relations between variables if a certain theory is correct, their statements are often in terms of one or more parameters expected to be larger or smaller than one or more other parameters.…
Descriptors: Researchers, Bayesian Statistics, Mathematical Concepts, Statistical Analysis
Testing Main Effects and Interactions in Latent Curve Analysis
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Curran, Patrick J.; Bauer, Daniel J.; Willoughby, Michael T. – Psychological Methods, 2004
A key strength of latent curve analysis (LCA) is the ability to model individual variability in rates of change as a function of 1 or more explanatory variables. The measurement of time plays a critical role because the explanatory variables multiplicatively interact with time in the prediction of the repeated measures. However, this interaction…
Descriptors: Multiple Regression Analysis, Predictive Measurement, Models, Item Response Theory