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A generalized Q--Q plot for longitudinal data

  • M. C. Pardo
  • R. Alonso
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    Most biomedical research is carried out using longitudinal studies. The method of generalized estimating equations (GEEs) introduced by Liang and Zeger [ Longitudinal data analysis using generalized linear models , Biometrika 73 (1986), pp. 13--22] and Zeger and Liang [ Longitudinal data analysis for discrete and continuous outcomes , Biometrics 42 (1986), pp. 121--130] has become a standard method for analyzing non-normal longitudinal data. Since then, a large variety of GEEs have been proposed. However, the model diagnostic problem has not been explored intensively. Oh et al. [ Modeldiagnostic plots for repeated measures data using the generalized estimating equations approach , Comput. Statist. Data Anal. 53 (2008), pp. 222--232] proposed residual plots based on the quantile--quantile (Q--Q) plots of the χ-super-2-distribution for repeated-measures data using the GEE methodology. They considered the Pearson, Anscombe and deviance residuals. In this work, we propose to extend this graphical diagnostic using a generalized residual. A simulation study is presented as well as two examples illustrating the proposed generalized Q--Q plots.

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    File URL: http://hdl.handle.net/10.1080/02664763.2012.710896
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    Article provided by Taylor & Francis Journals in its journal Journal of Applied Statistics.

    Volume (Year): 39 (2012)
    Issue (Month): 11 (July)
    Pages: 2349-2362

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    Handle: RePEc:taf:japsta:v:39:y:2012:i:11:p:2349-2362
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