An Extension of the Wilcoxon Rank-Sum Test for Complex Sample Survey Data

• Activity Number: 188
• Type: Contributed
• Date/Time: Monday, August 2, 2010 : 10:30 AM to 12:20 PM
• Sponsor: Section on Nonparametric Statistics
• 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
• Keywords: Population survey ; Score statistic ; weighted estimating equations ; Medical Expenditure Panel Survey

Abstract

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.