Nonlinear regression models for correlated count data
- 1 January 1992
- journal article
- Published by Wiley in Environmetrics
- Vol. 3 (2) , 211-222
- https://doi.org/10.1002/env.3170030206
Abstract
In this article, nonlinear regression models for correlated count data are examined. Correlation within clusters is modelled by a multivariate Gaussian mixing process on the log‐expectation scale. The regression parameters and the variance‐covariance parameters of the mixing process are estimated using quasi‐likelihood methods. An example involving temporal trends in hospital admissions for respiratory disease is used to illustrate the methods proposed.Keywords
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