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ERIC Number: EJ934206
Record Type: Journal
Publication Date: 2011-Jun
Pages: 17
Abstractor: As Provided
Reference Count: 40
ISSN: ISSN-1082-989X
Evaluating Models for Partially Clustered Designs
Baldwin, Scott A.; Bauer, Daniel J.; Stice, Eric; Rohde, Paul
Psychological Methods, v16 n2 p149-165 Jun 2011
Partially clustered designs, where clustering occurs in some conditions and not others, are common in psychology, particularly in prevention and intervention trials. This article reports results from a simulation comparing 5 approaches to analyzing partially clustered data, including Type I errors, parameter bias, efficiency, and power. Results indicate that multilevel models adapted for partially clustered data are relatively unbiased and efficient and consistently maintain the nominal Type I error rate when using appropriate degrees of freedom. To attain sufficient power in partially clustered designs, researchers should attend primarily to the number of clusters in the study. An illustration using data from a partially clustered eating disorder prevention trial is provided. (Contains 6 figures, 3 tables and 2 footnotes.)
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