The Relative Performance of Full Information Maximum Likelihood Estimation for Missing Data in Structural Equation Models.

Enders, Craig K.; Bandalos, Deborah L.

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Peer reviewed

ERIC Number: EJ636367

Record Type: Journal

Publication Date: 2001

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ISSN: ISSN-1070-5511

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The Relative Performance of Full Information Maximum Likelihood Estimation for Missing Data in Structural Equation Models.

Enders, Craig K.; Bandalos, Deborah L.

Structural Equation Modeling, v8 n3 p430-57 2001

Used Monte Carlo simulation to examine the performance of four missing data methods in structural equation models: (1)full information maximum likelihood (FIML); (2) listwise deletion; (3) pairwise deletion; and (4) similar response pattern imputation. Results show that FIML estimation is superior across all conditions of the design. (SLD)

Descriptors: Maximum Likelihood Statistics, Monte Carlo Methods, Simulation, Structural Equation Models

Publication Type: Journal Articles; Reports - Evaluative

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Audience: N/A

Language: English

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