Multiple hypothesis testing procedures with applications to epidemiologic studies

Epidemiologic and genetic studies often involve the testing of a large number of hypotheses with test statistics that are potentially dependent. In this project, we investigate multiple testing procedures to control the family-wise error rate and false discovery rate. We consider several classic and novel multiple hypothesis testing procedures. Furthermore, we compare the results of the procedures which take advantage of the dependent structure among test statistics to those of the procedures which do not. The data we used is from a case-control study of non-Hodgkin Lymphoma.