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Franco-Martínez, Alicia; Alvarado, Jesús M.; Sorrel, Miguel A. – Educational and Psychological Measurement, 2023
A sample suffers range restriction (RR) when its variance is reduced comparing with its population variance and, in turn, it fails representing such population. If the RR occurs over the latent factor, not directly over the observed variable, the researcher deals with an indirect RR, common when using convenience samples. This work explores how…
Descriptors: Factor Analysis, Factor Structure, Scores, Sampling
Kush, Joseph M.; Konold, Timothy R.; Bradshaw, Catherine P. – Grantee Submission, 2021
Multilevel structural equation (MSEM) models allow researchers to model latent factor structures at multiple levels simultaneously by decomposing within- and between-group variation. Yet the extent to which the sampling ratio (i.e., proportion of cases sampled from each group) influences the results of MSEM models remains unknown. This paper…
Descriptors: Sampling, Structural Equation Models, Factor Structure, Monte Carlo Methods
Md Desa, Zairul Nor Deana – ProQuest LLC, 2012
In recent years, there has been increasing interest in estimating and improving subscore reliability. In this study, the multidimensional item response theory (MIRT) and the bi-factor model were combined to estimate subscores, to obtain subscores reliability, and subscores classification. Both the compensatory and partially compensatory MIRT…
Descriptors: Item Response Theory, Computation, Reliability, Classification
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Buja, Andreas; Eyuboglu, Nermin – Multivariate Behavioral Research, 1992
Use of parallel analysis (PA), a selection rule for the number-of-factors problem, is investigated from the viewpoint of permutation assessment through a Monte Carlo simulation. Results reveal advantages and limitations of PA. Tables of sample eigenvalues are included. (SLD)
Descriptors: Computer Simulation, Correlation, Factor Structure, Mathematical Models
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Anderson, James C.; Gerbing, David W. – Psychometrika, 1984
This study of maximum likelihood confirmatory factor analysis found effects of practical significance due to sample size, the number of indicators per factor, and the number of factors for Joreskog and Sorbom's (1981) goodness-of-fit index (GFI), GFI adjusted for degrees of freedom, and the root mean square residual. (Author/BW)
Descriptors: Factor Analysis, Factor Structure, Goodness of Fit, Mathematical Models