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Power of the Likelihood Ratio Test in Covariance Structure Analysis
Abstract
A procedure for computing the power of the likelihood ratio test used in the context of covariance structure analysis is derived. The procedure uses statistics associated with the standard output of the computer programs commonly used and assumes that a specific alternative value of the parameter vector is specified. Using the noncentral Chi-square distribution, the power of the test is approximated by the asymptotic one for a sequence of local alternatives. The procedure is illustrated by an example. A Monte Carlo experiment also shows how good the approximation is for a specific case.
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Cited by
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Hu, L.-T., & Bentler, P. M. (1998) · Psychological Methods · doi:10.1037/1082-989x.3.4.424 · Cited by 12,298
Curran, P. J., West, S. G., & Finch, J. F. (1996) · Psychological Methods · doi:10.1037/1082-989x.1.1.16 · Cited by 5,512
Wolf, E. J., Harrington, K. M., Clark, S. L., & Miller, M. W. (2013) · Educational and Psychological Measurement · doi:10.1177/0013164413495237 · Cited by 3,931
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“…H0 model is invalid, however, the LRT—again assuming multivariate normality, a sufficiently large sample size, and several regularity conditions 1 (Satorra & Saris, 1985; Steiger et al., 1985)—asymptotically follows a noncentral χ 2 ( df , λ) distribution with non-centrality parameter λ and…”
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Metadata
- Authors
- Satorra, A., & Saris, W. E.
- Venue
- Psychometrika
- Publisher
- Cambridge University Press (CUP)
- Published
- 1985-03
- Volume
- 50
- Issue
- 1
- Pages
- 83-90
- ISSN
- 0033-3123 (ISSN-L)
- 1860-0980
- OpenAlex
- W2094817277
- Cited by
- 485
- References
- 0
- FWCI
- 13.49
- Type
- journal article
- Language
- en
- Open access
- closed
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