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ERIC Number: EJ932362
Record Type: Journal
Publication Date: 2010-Dec
Pages: 16
Abstractor: As Provided
Reference Count: 52
ISSN: ISSN-1082-989X
Expected versus Observed Information in SEM with Incomplete Normal and Nonnormal Data
Savalei, Victoria
Psychological Methods, v15 n4 p352-367 Dec 2010
Maximum likelihood is the most common estimation method in structural equation modeling. Standard errors for maximum likelihood estimates are obtained from the associated information matrix, which can be estimated from the sample using either expected or observed information. It is known that, with complete data, estimates based on observed or expected information are consistent. The situation changes with incomplete data. When the data are missing at random (MAR), standard errors based on expected information are not consistent, and observed information should be used. A less known fact is that in the presence of nonnormality, the estimated information matrix also enters the robust computations (both standard errors and the test statistic). Thus, with MAR nonnormal data, the use of the expected information matrix can potentially lead to incorrect robust computations. This article summarizes the results of 2 simulation studies that investigated the effect of using observed versus expected information estimates of standard errors and test statistics with normal and nonnormal incomplete data. Observed information is preferred across all conditions. Recommendations to researchers and software developers are outlined. (Contains 2 figures, 6 footnotes and 10 tables.)
American Psychological Association. Journals Department, 750 First Street NE, Washington, DC 20002-4242. Tel: 800-374-2721; Tel: 202-336-5510; Fax: 202-336-5502; e-mail:; Web site:
Publication Type: Journal Articles; Reports - Evaluative
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A