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Comment on “Wang et al. (2005), Robust estimating functions and bias correction for longitudinal data analysis”

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  • Nicola Lunardon
  • Giovanna Menardi

Abstract

This note provides a discussion on the manuscript by Wang et al. (2005) who aim to robustify inference for longitudinal data analysis by replacing the ordinary generalized estimating function with an influence‐bounded, possibly biased, version. To adjust for the bias of the ensuing robust estimator, the authors provide its analytic approximation by means of asymptotic expansions, and estimate it by plugging‐in a nonrobust estimate of the parameter of interest. In this letter, we argue that the proposed bias‐corrected estimator is, in fact, nonrobust.

Suggested Citation

  • Nicola Lunardon & Giovanna Menardi, 2020. "Comment on “Wang et al. (2005), Robust estimating functions and bias correction for longitudinal data analysis”," Biometrics, The International Biometric Society, vol. 76(3), pages 1040-1042, September.
    • Handle: RePEc:bla:biomet:v:76:y:2020:i:3:p:1040-1042
    DOI: 10.1111/biom.13263
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    References listed on IDEAS

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    1. You-Gan Wang & Xu Lin & Min Zhu, 2005. "Robust Estimating Functions and Bias Correction for Longitudinal Data Analysis," Biometrics, The International Biometric Society, vol. 61(3), pages 684-691, September.
    2. P. Diggle & M. G. Kenward, 1994. "Informative Drop‐Out in Longitudinal Data Analysis," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 43(1), pages 49-73, March.
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    Cited by:

    1. You‐Gan Wang & Xu Lin & Min Zhu, 2020. "Rejoinder to “Comment on ‘Wang et al. (2005), Robust estimating functions and bias correction for longitudinal data analysis’ by Nicola Lunardon and Giovanna Menardi”," Biometrics, The International Biometric Society, vol. 76(3), pages 1043-1044, September.

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