Speaker:
Zeny Feng, University of Guelph

Title: Estimation of the proportion of true null hypotheses when testing a large
number

of hypotheses

Abstract:

When testing a large number of hypotheses, the problem of

estimating the proportion of true null hypotheses, pi_0, is often of

interest. The estimation of pi_0 becomes a common and practical

problem as modern scientific experiments often involve testing

hundreds and thousands of null hypotheses. In this talk, we first

review several widely used estimators based on threshold methods

and nonparametric maximum likelihood estimation of the p-value

density. The current estimators are all derived under the

assumption of independent test statistics. We compare their

performances through simulation studies. In reality, especially in

cDNA microarray data analysis, there is often strong dependence

among test statistics. We propose data-driven estimators for pi_0 by

incorporating the distribution pattern of the observed p-values

without the assumption of independence. We evaluate and

compare our proposed estimators with others through simulation

studies. We also analyze real data for illustration.