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Lin, Johnny; Bentler, Peter M. – Multivariate Behavioral Research, 2012
Goodness-of-fit testing in factor analysis is based on the assumption that the test statistic is asymptotically chi-square, but this property may not hold in small samples even when the factors and errors are normally distributed in the population. Robust methods such as Browne's (1984) asymptotically distribution-free method and Satorra Bentler's…
Descriptors: Factor Analysis, Statistical Analysis, Scaling, Sample Size
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Olivera-Aguilar, Margarita; Millsap, Roger E. – Multivariate Behavioral Research, 2013
A common finding in studies of differential prediction across groups is that although regression slopes are the same or similar across groups, group differences exist in regression intercepts. Building on earlier work by Birnbaum (1979), Millsap (1998) presented an invariant factor model that would explain such intercept differences as arising due…
Descriptors: Statistical Analysis, Measurement, Prediction, Regression (Statistics)
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Maydeu-Olivares, Alberto; Brown, Anna – Multivariate Behavioral Research, 2010
The comparative format used in ranking and paired comparisons tasks can significantly reduce the impact of uniform response biases typically associated with rating scales. Thurstone's (1927, 1931) model provides a powerful framework for modeling comparative data such as paired comparisons and rankings. Although Thurstonian models are generally…
Descriptors: Item Response Theory, Rating Scales, Models, Comparative Analysis
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MacCallum, Robert C.; Widaman, Keith F.; Preacher, Kristopher J.; Hong, Sehee – Multivariate Behavioral Research, 2001
Examined the effects of sample size and other design features on correspondence between factors obtained from analysis of sample data and those present in the population from which the samples were drawn, examining these phenomena in the situation in which the common factor model does not hold exactly in the population. Tested a theoretical…
Descriptors: Error of Measurement, Factor Analysis, Goodness of Fit, Models
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Kaplan, David – Multivariate Behavioral Research, 1990
A strategy for evaluating/modifying covariance structure models (CSMs) is presented. The approach uses recent developments in estimation under nonstandard conditions and unified asymptotic theory related to hypothesis testing, and it determines the extent of sample size sensitivity and specification error effects by relying on existing statistical…
Descriptors: Error of Measurement, Estimation (Mathematics), Evaluation Methods, Goodness of Fit