Date of Award
11-30-2007
Degree Type
Thesis
Degree Name
Master of Science (MS)
Department
Mathematics and Statistics
First Advisor
Yu-Sheng Hsu - Co-Chair
Second Advisor
Jiawei Liu - Co-Chair
Third Advisor
Yichuan Zhao
Abstract
Model credibility index is defined to be a sample size under which the power of rejection equals 0.5. It applies goodness-of-fit testing thinking and uses a one-number summary statistic as an assessment tool in a false model world. The estimation of the model credibility index involves a bootstrap resampling technique. To assess the consistency of the estimator of model credibility index, we instead study the variance of the power achieved at a fixed sample size. An improved subsampling method is proposed to obtain an unbiased estimator of the variance of power. We present two examples to interpret the mechanics of building model credibility index and estimate its error in model selection. One example is two-way independent model by Pearson Chi-square test, and another example is multi-dimensional logistic regression model using likelihood ratio test.
DOI
https://doi.org/10.57709/1059695
Recommended Citation
Xiao, Yan, "Evaluating Variance of the Model Credibility Index." Thesis, Georgia State University, 2007.
doi: https://doi.org/10.57709/1059695