Physical Sciences and Mathematics Commons^™

Evaluation Of Factors Impacting Predictor Importance Results In Multilevel Models, Soonhwa (Suna) Paek

Theses and Dissertations

Background: Dominance Analysis (DA) was originally proposed to determine the relative importance of predictor variables in OLS regression models by comparing the change in model fit (i.e., R2) resulting from adding each predictor to each possible subset model (Azen & Budescu, 2003; Azen, 2013; Budescu, 1993). Although various educational studies show that DA can provide useful information in research, the DA procedure has not been studied extensively with Multilevel Linear Models (MLMs), which are commonly used to analyze nested data structures.

Purpose: This study aimed to identify appropriate multilevel measures of fit for the DA procedure in various MLMs, and …

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 …