Goodness-of-fit tests of generalized linear mixed models for repeated ordinal responses

ABSTRACT

Categorical longitudinal data are frequently applied in a variety of fields, and are commonly fitted by generalized linear mixed models (GLMMs) and generalized estimating equations models. The cumulative logit is one of the useful link functions to deal with the problem involving repeated ordinal responses. To check the adequacy of the GLMMs with cumulative logit link function, two goodness-of-fit tests constructed by the unweighted sum of squared model residuals using numerical integration and bootstrap resampling technique are proposed. The empirical type I error rates and powers of the proposed tests are examined by simulation studies. The ordinal longitudinal studies are utilized to illustrate the application of the two proposed tests.

KEYWORDS:

• Bootstrap resampling
• generalized linear mixed model
• goodness-of-fit
• longitudinal ordinal response
• numerical integration

Acknowledgments

The authors gratefully thank to the reviewers for their valuable comments and constructive suggestions on the original manuscript, which led to substantial improvements in this article.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The research was supported in part by Ministry of Science and Technology in Taiwan NSC-102-2118-M-165-001.