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Functional response models for intraclass correlation coefficients

Author

Listed:
  • N. Lu
  • T. Chen
  • P. Wu
  • D. Gunzler
  • H. Zhang
  • H. He
  • X.M. Tu

Abstract

Intraclass correlation coefficients (ICC) are employed in a wide range of behavioral, biomedical, psychosocial, and health care related research for assessing reliability of continuous outcomes. The linear mixed-effects model (LMM) is the most popular approach for inference about the ICC. However, since LMM is a normal distribution-based model and non-normal data are the norm rather than the exception in most studies, its applications to real study data always beg the question of inference validity. In this paper, we propose a distribution-free alternative to provide robust inference based on the functional response models. We illustrate the performance of the new approach using both real and simulated data.

Suggested Citation

  • N. Lu & T. Chen & P. Wu & D. Gunzler & H. Zhang & H. He & X.M. Tu, 2014. "Functional response models for intraclass correlation coefficients," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(11), pages 2539-2556, November.
    • Handle: RePEc:taf:japsta:v:41:y:2014:i:11:p:2539-2556
    DOI: 10.1080/02664763.2014.920780
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    References listed on IDEAS

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