Date of Award

5-1-2019

Degree Name

Doctor of Philosophy

Department

Quantitative Methods

First Advisor

Koran, Jennifer

Abstract

This study introduces a new model-free case influence measure (DOCR) to the SEM field and evaluates its performance compared to that of Mahalanobis Distance (MD) and Generalized Cook’s Distance (gCD) when the sample size, proportion of target cases to non-target cases, and type of model used to generate the data are manipulated. The findings suggest the DOCR measure generally performed better than MD and gCD in identifying the target cases across all simulated conditions. However, the performance of the DOCR measure under small sample size was not satisfactory, and it raised a red flag about the sensitivity of this measure to small sample sizes. Therefore, researchers and practitioners should only use the DOCR measure with sufficiently large sample sizes, but not larger than 600.

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