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Bootstrapping longitudinal data with multiple levels of variation

Author

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  • O’Shaughnessy, P.Y.
  • Welsh, A.H.

Abstract

A set of estimators for model parameters in the framework of linear mixed models is considered for longitudinal data with multiple levels of random variation. Various bootstrap methods are assessed for making inference about the parameters including the variance components for which, typically, bootstrap confidence intervals show undercoverage. A new weighted estimating equation bootstrap, which uses different weight schemes for different parameter estimators, is proposed. It shows improved variance estimation for the variance component estimators and produces confidence intervals with better coverage for the variance components in cases with normal and non-normal errors.

Suggested Citation

  • O’Shaughnessy, P.Y. & Welsh, A.H., 2018. "Bootstrapping longitudinal data with multiple levels of variation," Computational Statistics & Data Analysis, Elsevier, vol. 124(C), pages 117-131.
    • Handle: RePEc:eee:csdana:v:124:y:2018:i:c:p:117-131
    DOI: 10.1016/j.csda.2018.02.004
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    References listed on IDEAS

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    1. Samanta, Mayukh & Welsh, A.H., 2013. "Bootstrapping for highly unbalanced clustered data," Computational Statistics & Data Analysis, Elsevier, vol. 59(C), pages 70-81.
    2. Brajendra C. Sutradhar & Kalyan Das, 2000. "On the Accuracy of Efficiency of Estimating Equation Approach," Biometrics, The International Biometric Society, vol. 56(2), pages 622-625, June.
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    4. You-Gan Wang & Vincent J. Carey, 2004. "Unbiased Estimating Equations From Working Correlation Models for Irregularly Timed Repeated Measures," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 845-853, January.
    5. Field, C. A. & Pang, Zhen & Welsh, A. H., 2010. "Bootstrapping Robust Estimates for Clustered Data," Journal of the American Statistical Association, American Statistical Association, vol. 105(492), pages 1606-1616.
    6. C. A. Field & A. H. Welsh, 2007. "Bootstrapping clustered data," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 69(3), pages 369-390, June.
    7. Salibian-Barrera, Matias & Van Aelst, Stefan, 2008. "Robust model selection using fast and robust bootstrap," Computational Statistics & Data Analysis, Elsevier, vol. 52(12), pages 5121-5135, August.
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    Cited by:

    1. Flores-Agreda, Daniel & Cantoni, Eva, 2019. "Bootstrap estimation of uncertainty in prediction for generalized linear mixed models," Computational Statistics & Data Analysis, Elsevier, vol. 130(C), pages 1-17.

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