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Abstract Details

Activity Number: 188
Type: Contributed
Date/Time: Monday, August 2, 2010 : 10:30 AM to 12:20 PM
Sponsor: Section on Nonparametric Statistics
Abstract - #308217
Title: An Extension of the Wilcoxon Rank-Sum Test for Complex Sample Survey Data
Author(s): Sundareshwaran Natarajan*+ and Stuart R. Lipsitz and Debajyoti Sinha and Garrett Fitzmaurice
Companies: U.S. Department of Veterans Affairs and Brigham and Women's Hospital and Florida State University and Harvard Medical School
Address: 423 E 23rd Street, New York, NY, 10010,
Keywords: Population survey ; Score statistic ; weighted estimating equations ; Medical Expenditure Panel Survey

Complex survey sampling is used to sample a fraction of a large finite population. While the Wilcoxon rank sum test is commonly used to compare an ordinal variable in bivariate analyses, no simple extension of the Wilcoxon rank sum test has been proposed for complex survey data. With a simple random sample of independent subjects, the Wilcoxon rank-sum test statistic equals the score test statistic for the group effect from a proportional-odds cumulative logistic regression model for an ordinal outcome. Using this regression framework, for complex survey data, we formulate a similar proportional-odds cumulative logistic regression model for the ordinal variable, and use an estimating equations score statistic for no group effect as an extension of the Wilcoxon test. The proposed method is applied to a complex survey designed to produce national estimates of the health care use and costs.

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