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ERIC Number: EJ788251
Record Type: Journal
Publication Date: 2008-Mar
Pages: 9
Abstractor: Author
Reference Count: 0
ISSN: ISSN-0012-1649
Temporal Patterns of Variable Relationships in Person-Oriented Research: Longitudinal Models of Configural Frequency Analysis
von Eye, Alexander; Mun, Eun Young; Bogat, G. Anne
Developmental Psychology, v44 n2 p437-445 Mar 2008
This article reviews the premises of configural frequency analysis (CFA), including methods of choosing significance tests and base models, as well as protecting [alpha], and discusses why CFA is a useful approach when conducting longitudinal person-oriented research. CFA operates at the manifest variable level. Longitudinal CFA seeks to identify those temporal patterns that stand out as more frequent (CFA types) or less frequent (CFA antitypes) than expected with reference to a base model. A base model that has been used frequently in CFA applications, prediction CFA, and a new base model, auto-association CFA, are discussed for analysis of cross-classifications of longitudinal data. The former base model takes the associations among predictors and among criteria into account. The latter takes the auto-associations among repeatedly observed variables into account. Application examples of each are given using data from a longitudinal study of domestic violence. It is demonstrated that CFA results are not redundant with results from log-linear modeling or multinomial regression and that, of these approaches, CFA shows particular utility when conducting person-oriented research.
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: Researchers
Language: English
Sponsor: N/A
Authoring Institution: N/A