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On the robustness of weighted methods for fitting models to case-control data

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  • Alastair Scott
  • Chris Wild

Abstract

We compare the robustness under model misspecification of two approaches to fitting logistic regression models with unmatched case-control data. One is the standard survey approach based on weighted versions of population estimating equations. The other is the likelihood-based approach that is standard in medical applications. The conventional view is that the (less efficient) survey-weighted approach leads to greater robustness. We conclude that this view is not always justified. Copyright 2002 The Royal Statistical Society.

Suggested Citation

  • Alastair Scott & Chris Wild, 2002. "On the robustness of weighted methods for fitting models to case-control data," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(2), pages 207-219.
  • Handle: RePEc:bla:jorssb:v:64:y:2002:i:2:p:207-219
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    References listed on IDEAS

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    1. Manski, Charles F. & Thompson, T. Scott, 1989. "Estimation of best predictors of binary response," Journal of Econometrics, Elsevier, vol. 40(1), pages 97-123, January.
    2. Yu Xie & Charles F. Manski, 1989. "The Logit Model and Response-Based Samples," Sociological Methods & Research, , vol. 17(3), pages 283-302, February.
    3. J. F. Lawless & J. D. Kalbfleisch & C. J. Wild, 1999. "Semiparametric methods for response-selective and missing data problems in regression," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(2), pages 413-438.
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    Cited by:

    1. Robert B. Nielsen & Martin C. Seay, 2014. "Complex Samples and Regression-Based Inference: Considerations for Consumer Researchers," Journal of Consumer Affairs, Wiley Blackwell, vol. 48(3), pages 603-619, October.
    2. Alan Lee & Yuichi Hirose, 2010. "Semi-parametric efficiency bounds for regression models under response-selective sampling: the profile likelihood approach," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 62(6), pages 1023-1052, December.
    3. Yanyuan Ma & Raymond J. Carroll, 2016. "Semiparametric estimation in the secondary analysis of case–control studies," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(1), pages 127-151, January.

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