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Methods for Analyzing Secondary Outcomes in Public Health Case–Control Studies

  • Elizabeth D. Schifano
  • Haim Bar
  • Ofer HarelEmail author
Part of the ICSA Book Series in Statistics book series (ICSABSS)

Abstract

Case–control studies are common in public health research. In these studies, cases are chosen based on the primary outcome but there are usually many other related variables which are collected. While the analysis of the association between the primary outcome and exposure variables is generally the main focus of the study, the association between secondary outcomes and exposure variables may also be of interest. Since the experiment was designed for the analysis of the primary outcome, the analysis of secondary outcomes may suffer from selection bias. In this chapter we will introduce the problem and the potential biased inference that can result from ignoring the sampling design. We will discuss and compare a design-based and model-based approach to account for the bias, and demonstrate the methods using a public health data set.

Keywords

Secondary Outcome Propensity Score Smoking Behavior Propensity Score Match Inverse Probability Weighting 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

The authors wish to thank Dr. David C. Christiani for generously sharing his data. This research was supported in part by the National Institute of Mental Health, Award Number K01MH087219. The content of this paper is solely the responsibility of the authors, and it does not represent the official views of the National Institute of Mental Health or the National Institutes of Health.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Department of StatisticsUniversity of ConnecticutStorrsUSA

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