Estimation of the Squared Population Cross-Validity Under Conditions of Predictor Selection

<p>The current study employed a Monte Carlo design to examine whether samplebased and formula-based estimates of cross-validated R2 differ in accuracy when predictor selection is and is not performed. Analyses were conducted on three datasets with 5, 10, or 15 predictors and different predictor-criterion relationships. Results demonstrated that, in most cases, a formula-based estimate of the cross-validated R2 was as accurate as a sample-based estimate. The one exception was the five predictor case wherein the formula-based estimate exhibited substantially greater bias than the estimate from a sample-based cross validation study. Thus, formula-based estimates, which have an enormous practical advantage over a two sample cross validation study, can be used in most cases without fear of greater error.</p>

Name thesis:degree_name

Master of Science

Discipline thesis:degree_discipline

Department of Psychological Sciences

Year

2015

Author dc:creator

• Kircher, Andrew J.

Contributors dc:contributor

• Reagan D. Brown (Director), Elizabeth L. Shoenfelt, Amber N. Schroeder

• Predictor
• Criterion
• Formula
• Based
• Applied Behavior Analysis
• Psychology

Repository record dc:identifier

https://digitalcommons.wku.edu/theses/1472

OAI identifier oai:identifier

oai:digitalcommons.wku.edu:theses-2475