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Huo, Yan; Budescu, David V. – Multivariate Behavioral Research, 2009
Dominance analysis (Budescu, 1993) offers a general framework for determination of relative importance of predictors in univariate and multivariate multiple regression models. This approach relies on pairwise comparisons of the contribution of predictors in all relevant subset models. In this article we extend dominance analysis to canonical…
Descriptors: Multivariate Analysis, Correlation, Regression (Statistics), Models
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Hayes, Andrew F.; Preacher, Kristopher J. – Multivariate Behavioral Research, 2010
Most treatments of indirect effects and mediation in the statistical methods literature and the corresponding methods used by behavioral scientists have assumed linear relationships between variables in the causal system. Here we describe and extend a method first introduced by Stolzenberg (1980) for estimating indirect effects in models of…
Descriptors: Computation, Methods, Models, Statistical Analysis
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Cohen, Ayala; Nahum-Shani, Inbal; Doveh, Etti – Multivariate Behavioral Research, 2010
In their seminal paper, Edwards and Parry (1993) presented the polynomial regression as a better alternative to applying difference score in the study of congruence. Although this method is increasingly applied in congruence research, its complexity relative to other methods for assessing congruence (e.g., difference score methods) was one of the…
Descriptors: Behavioral Sciences, Evaluation Methods, Social Sciences, Social Support Groups
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Overall, John E.; Tonidandel, Scott – Multivariate Behavioral Research, 2010
A previous Monte Carlo study examined the relative powers of several simple and more complex procedures for testing the significance of difference in mean rates of change in a controlled, longitudinal, treatment evaluation study. Results revealed that the relative powers depended on the correlation structure of the simulated repeated measurements.…
Descriptors: Monte Carlo Methods, Statistical Significance, Correlation, Depression (Psychology)
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O'Grady, Kevin E.; Medoff, Deborah R. – Multivariate Behavioral Research, 1988
Limitations of dummy coding and nonsense coding as methods of coding categorical variables for use as predictors in multiple regression analysis are discussed. The combination of these approaches often yields estimates and tests of significance that are not intended by researchers for inclusion in their models. (SLD)
Descriptors: Multiple Regression Analysis, Predictive Measurement, Regression (Statistics), Research Problems