Statistics Seminar

Su Mo Tu We Th Fr Sa
31 1 2 3 4 5 6
7 8 9 10 11 12 13
14 15 16 17 18 19 20
21 22 23 24 25 26 27
28 29 1 2 3 4 5
Date/Time:Monday, 01 Feb 2016 from 4:10 pm to 5:00 pm
Location:Snedecor 3105
Cost:Free
URL:www.stat.iastate.edu
Contact:Denise Riker
Phone:515-294-1076
Channel:College of Liberal Arts and Sciences
Categories:Lectures
Actions:Download iCal/vCal | Email Reminder
Multiple Testing with Heterogeneous Multinomial Distributions, Joshua Habiger, Department of Statistics, Oklahoma State University, Stillwater

False discovery rate (FDR) procedures provide misleading inference when testing multiple null hypotheses with heterogeneous multinomial data. For example, in the motivating study the goal is to identify species of bacteria near the roots of wheat plants (rhizobacteria) that are associated with productivity, but standard procedures discover the most abundant species even when the association is weak or negligible, and fail to discover strong associations when species are not abundant. Consequently, a list of abundant species is produced by the multiple testing procedure even though the goal was to provide a list of productivity-associated species. This talk provides an FDR method based on mixtures of multinomial distributions and shows that it tends to discover more non-negligible effects and fewer negligible effects when the data are heterogeneous across tests. The proposed method and competing methods are applied to the motivating data. The new method identifies more species that are strongly associated with productivity and identifies fewer species that are weakly associated with productivity.