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The robustness of estimates of total indirect effects in covariance structure models estimated by maximum

The robustness of estimates of total indirect effects in covariance structure models estimated by... Abstract The large sample distribution of total indirect effects in covariance structure models in well known. Using Monte Carlo methods, this study examines the applicability of the large sample theory to maximum likelihood estimates oftotal indirect effects in sample sizes of 50, 100, 200, 400, and 800. Two models are studied. Model 1 is a recursive model with observable variables and Model 2 is a nonrecursive model with latent variables. For the large sample theory to apply, the results suggest that sample szes of 200 or more and 400 or more are required for models such as Model 1 and Model 2, respectively. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Psychometrika Springer Journals

The robustness of estimates of total indirect effects in covariance structure models estimated by maximum

Psychometrika , Volume 55 (2): 16 – Jun 1, 1990

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References (55)

Publisher
Springer Journals
Copyright
1990 The Psychometric Society
ISSN
0033-3123
eISSN
1860-0980
DOI
10.1007/BF02295291
Publisher site
See Article on Publisher Site

Abstract

Abstract The large sample distribution of total indirect effects in covariance structure models in well known. Using Monte Carlo methods, this study examines the applicability of the large sample theory to maximum likelihood estimates oftotal indirect effects in sample sizes of 50, 100, 200, 400, and 800. Two models are studied. Model 1 is a recursive model with observable variables and Model 2 is a nonrecursive model with latent variables. For the large sample theory to apply, the results suggest that sample szes of 200 or more and 400 or more are required for models such as Model 1 and Model 2, respectively.

Journal

PsychometrikaSpringer Journals

Published: Jun 1, 1990

Keywords: Psychometrics; Assessment, Testing and Evaluation; Statistics for Social Sciences, Humanities, Law; Statistical Theory and Methods

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