Online Program Home
My Program

Abstract Details

Activity Number: 35
Type: Contributed
Date/Time: Sunday, July 31, 2016 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistics in Epidemiology
Abstract #320243
Title: Optimum Sample Size Allocation in Multilevel Disease Detection Problem
Author(s): Yinan Fang* and Chong Wang and Jeffrey Zimmerman
Companies: Iowa State University and Iowa State University and Iowa State University
Keywords: Disease detection ; Detection probability ; Sample size allocation ; Multi-level Hierarchical Structure

Animal husbandry all over the world has to deal with the problems coming from outbreaks of certain epidemics every year. To detect the presence of an infectious disease in the target population plays the crucial role of disease surveillance. The main intention of this paper is to find the optimum sampling strategy in a multilevel structure to maximize the detection probability given limited sample size. In this paper, detection probability is calculated under the assumption that test result is binomially distributed. First, we show that in a simple two-level structure, assigning total sample size equally to each unit is the best sampling scheme. After that, the discussion is expanded to balanced hierarchical structure. And we show that under certain regularity conditions, equal allocation to the lowest-level unit will maximize the detection probability. Furthermore, in the case of unbalanced multi-level structure, it is demonstrated that equal allocation of total sample to any level units may not be the optimum sampling scheme as in the balanced structure.

Authors who are presenting talks have a * after their name.

Back to the full JSM 2016 program

Copyright © American Statistical Association