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Inference in semi-parametric spline mixed models for longitudinal data

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  • Sanjoy Sinha
  • Abdus Sattar

Abstract

In this paper, the authors investigate a robust semi-parametric mixed effects model for analyzing longitudinal data with an unspecified mean response function. The robust method, developed in the framework of the maximum likelihood, is used to bound the influence of potential outliers when estimating the model parameters. The authors also present a robust test procedure for assessing the significance of a variance component in the mixed model. An application is provided using a clinical dataset from a retinopathy of prematurity study in which longitudinal measurements were obtained from premature infants treated with supplemental oxygen. The empirical properties of the proposed estimators are also studied in simulations. Copyright Sapienza Università di Roma 2015

Suggested Citation

  • Sanjoy Sinha & Abdus Sattar, 2015. "Inference in semi-parametric spline mixed models for longitudinal data," METRON, Springer;Sapienza Università di Roma, vol. 73(3), pages 377-395, December.
    • Handle: RePEc:spr:metron:v:73:y:2015:i:3:p:377-395
    DOI: 10.1007/s40300-015-0059-2
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    References listed on IDEAS

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