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ERIC Number: ED406438
Record Type: Non-Journal
Publication Date: 1997-Jan-25
Pages: 18
Abstractor: N/A
Reference Count: N/A
ISBN: N/A
ISSN: N/A
Interpretation of Structure Coefficients Can Prevent Erroneous Conclusions about Regression Results.
Whitaker, Jean S.
The increased use of multiple regression analysis in research warrants closer examination of the coefficients produced in these analyses, especially ones which are often ignored, such as structure coefficients. Structure coefficients are bivariate correlation coefficients between a predictor variable and the synthetic variable. When predictor variables are correlated with each other, regression results may be seriously distorted by failure to interpret structure coefficients. Structure coefficients have analogues in all analyses (e.g., canonical analysis, factor analysis, and discriminant analysis) and should be interpreted in all analyses. Several examples of research in which not examining structure coefficients led to misinterpreting results are cited. A small heuristic example is presented to provide a concrete example of how interpretation of regression results might differ when predictor variables are correlated with each other. The astute researcher should examine both beta weights and structure coefficients when interpreting regression results with correlated predictor variables. (Contains 1 figure, 1 table, and 27 references.) (Author/SLD)
Publication Type: Reports - Evaluative; Speeches/Meeting Papers
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A