Functional response models for intraclass correlation coefficients

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.

Keywords:

• domain-sampling model
• generalized estimating equations
• linear mixed-effects model
• SF-36
• U-statistics-based generalized estimating equations