Multiple Comparisons for a Psychophysical Test in Bootstrap Logistic Regression

Abstract

We propose an algorithm of multiple comparisons with a control for a psychophysical test. Our algorithm is based on the step-down procedure and is applicable to the bootstrap test in logistic regression. We use logistic regression combined with guessing rate and log-likelihood ratio test statistics of multiple samples in order to test hypotheses by using non-parametric bootstrap resampling. We apply our algorithm to visual acuity measurement, and show that bootstrap resampling can be used to resolve problems with multiple comparisons especially when the numbers of observations among samples are not identical.