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The Effects of Sampling Error and Model Characteristics on Parameter Estimation for Maximum Likelihood Confirmatory Factor Analysis

Gerbing, David W., Anderson, James C.·1985·Multivariate Behavioral Research

Abstract

Monte Carlo methods were used to systematically study the effects of sampling error and model characteristics upon parameter estimates and their associated standard errors in maximum likelihood confirmatory factor analysis. Sample sizes were varied from 50 to 300 for models defined by different numbers of indicators per factor, numbers of factors, correlations between factors, and indicator reliabilities. The measurement and structural parameter estimates were generally unbiased except for the structural parameters relating factors defined by only two indicators. Sampling variability can be quite large, though, particularly as sample size becomes smaller, there are fewer indicators per factor and the reliabilities are lower. However, the estimated standard errors were adjusted accordingly.

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Metadata

Authors
Gerbing, D. W., & Anderson, J. C.
Venue
Multivariate Behavioral Research
Published
1985-07
Volume
20
Issue
3
Pages
255-271
ISSN
  • 0027-3171 (ISSN-L)
  • 1532-7906
OpenAlex
W2053321261
Cited by
266
References
0
FWCI
6.42
Type
journal article
Language
en
Open access
closed

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Gerbing, D. W., & Anderson, J. C. (1985). The Effects of Sampling Error and Model Characteristics on Parameter Estimation for Maximum Likelihood Confirmatory Factor Analysis. Multivariate Behavioral Research. https://doi.org/10.1207/s15327906mbr2003_2

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