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Inferential Procedures For Dominance Analysis Measures In Multiple Regression, Shuwen Tang

Theses and Dissertations

In order to better interpret a selected multiple regression model, researchers are often interested in whether a predictor is significantly more important than another or not. This study investigates the performance of the Normal-Theory based (asymptotic) confidence interval and bootstrap confidence intervals for predictors' dominance relationships using both normal and non-normal data. The results show that asymptotic confidence interval method is adequate to make inferences for comparing two general dominance measures when the distribution is multivariate normal or slightly non-normal and when the effect size is no less than 0.15 and the sample size is at least 100. However, the …