2001
DOI: 10.1177/0013164401612006
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Use of Structure Coefficients in Published Multiple Regression Articles: β is not Enough

Abstract: The importance of interpreting structure coefficients throughout the General Linear Model (GLM) is widely accepted. However, regression researchers too infrequently consult regression structure coefficients to augment their interpretations. The authors reviewed articles published in the Journal of Applied Psychology to determine how interpretations might have differed if standardized regression coefficients and structure coefficients (or else bivariate rs of predictors with the criterion) had been interpreted.… Show more

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Cited by 358 publications
(120 citation statements)
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References 27 publications
(30 reference statements)
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“…For each type of work-related learning, separate analyses were performed. The standardized regression weights (ß's) and R 2 values were supplemented by structure coefficients (r s ) that are not suppressed or inflated by collinearity (Courville & Thompson, 2001).…”
Section: Discussionmentioning
confidence: 99%
“…For each type of work-related learning, separate analyses were performed. The standardized regression weights (ß's) and R 2 values were supplemented by structure coefficients (r s ) that are not suppressed or inflated by collinearity (Courville & Thompson, 2001).…”
Section: Discussionmentioning
confidence: 99%
“…Need satisfaction scores were rated on different scales so this model tested whether perceived autonomy-supportive coaching behaviors predicted contrasts between need satisfaction in general and need satisfaction with athletes' relationships with their coaches. Given the expected collinearity between predictors in each of these models, structure coefficients were given greater emphasis than standardized regression coefficients when interpreting parameter estimates in these models (Courville & Thompson, 2001;Thompson & Borello, 1985).…”
Section: Discussionmentioning
confidence: 99%
“…This, according to Courville and Thompson (2001), is useful to determine if there is shared variance and suppressors in the regression. A benefi cial property of the structure coeffi cient is that it is not affected by associations between independent variables, as a structure coeffi cient is simply a Pearson r between independent variable and dependent variable (Courville and Thompson, 2001). However, the structural coeffi cient cannot tell us which variables share this variance.…”
Section: Determinants Of Physical Availability Of Food: Aggregate Anamentioning
confidence: 99%