The problem of multiple comparisons arises when performing many hypothesis tests, in which case the “familywise error rate” or chance of one or more incorrect significant findings among all these tests increases with the number of tests being performed.  Professor Logan has a keen interest in this area in which he continues to publish new methods and applications.  Working with Prof. Rowe,  Prof. Logan has investigated multiple comparison thresholding techniques in single-subject fMRI analysis.  Professor Logan's work with Professor Tamhane at Northwestern University includes the problem of comparing two treatments at multiple endpoints and multiple comparison procedures to identify the minimum effective dose and/or maximum safe dose in the dose-response setting.  In collaboration with Professor Zhang, Dr. Logan has investigated methods for controlling the familywise error rate when performing pairwise comparisons among several groups when the outcome is the time to an event of interest. 

Back to Biostatistics Research Areas