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Importance of Adjusting for Multi-stage Design When Analyzing Data from Complex Surveys

  • Trung Ha
  • Julia N. Soulakova
Chapter
Part of the ICSA Book Series in Statistics book series (ICSABSS)

Abstract

Social scientists and policy makers commonly use estimates derived from population-based studies, e.g., estimates derived from the Tobacco Use Supplement (TUS) are commonly used in behavioral studies targeted on smoking and quitting behaviors. The U.S. Census Bureau and other agencies designing and administering national surveys provide technical guidelines on suitable statistical methodologies. The guidelines specify the appropriate methods for estimation and prediction. However, when performing secondary data analyses scientists may be prone to simplify analytical strategies and use classical statistical methods, i.e., ignore design specifics and mistreat the complex design used to gather the data as simple random sampling. In this chapter, we illustrate the importance of using the guidelines when analyzing complex surveys. We discuss three methods: method I ignores any weighting, method II incorporates the main weight only, and method III utilizes the main weight and balanced repeated replications with specified replicate weights. We illustrate possible discrepancies in point estimates and standard errors using 2014–2015 TUS data. Presented examples include smoking status, attitudes toward smoking restrictions in public places and cars, and smoking rules at home among single parents in the USA.

Keywords

Balanced Repeated Replication Complex sampling Complex survey Current Population Survey Fay’s factor Hadamard matrix Multistage sampling National Health Interview Survey Primary sampling unit Replicate weights Single-parent household Smoke-free home Smoke-free workplace Stratum Successive Difference Replication Taylor Linearization Tobacco Use Supplement Ultimate Sampling Unit Unequal probability sampling Variance estimation 

Notes

Acknowledgments

We are thankful to James Holland, College of Medicine, University of Central Florida, for helping us improve the chapter.

Funding: Research reported in this publication was supported by the National Institute on Minority Health and Health Disparities of the National Institutes of Health under Award Number R01MD009718. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Burnett School of Biomedical SciencesCollege of Medicine, University of Central FloridaOrlandoUSA

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