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Activity Number: 531 - SPEED: Statistical Computing: Methods, Implementation, and Application, Part 2
Type: Contributed
Date/Time: Wednesday, July 31, 2019 : 11:35 AM to 12:20 PM
Sponsor: Section on Statistical Computing
Abstract #307946
Title: Exact Inference for Analyzing Contingency Tables in Finite Populations
Author(s): Shiva Dibaj* and Gregory Wilding and Graham Warren
Companies: UT MD Anderson Cancer Center and SUNY at Buffalo and University of Kentucky
Keywords: Exact test; Hypergeometric; Categorical data; Computation; Finite population; Survey sample

With recent developments in computer power the application of exact inferential methods has become more feasible which has resulted in increasing popularity of these approaches. However, there is a lack of such methodology for populations with more complex structure, such as finite populations. When a small sample is drawn from a finite population, the number of individuals with a specific characteristic of interest follows hypergeometric distribution. In order to test for the comparison of two proportions in finite populations we develop an exact unconditional test. To calculate the exact p-value, all possible realizations of the test statistic along with their probabilities are determined. We utilize the information gained from the sample to restrict our search for the maximum p-value. Our proposed test has power equal to its competitors while maintains the pre-specified nominal significance level.

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

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