Analyzing repeated measures on generalized linear models via the bootstrap. (English) Zbl 0707.62250

Moulton, Lawrence H.; Zeger, Scott L.

Biometrics 45, No. 2, 381-394 (1989).

Summary: The analysis of longitudinal data for which the response variables have nonnormal error distributions previously has been complex and/or dependent on restrictive assumptions. In this paper simple methods are introduced for the class of generalized linear models (GLMs). Regressions are fit to the data at each observation time; functions of the resulting coefficients may be bootstrapped, or the coefficients combined through closed-form estimation of their covariances. Application is made to a data set on xerophthalmia in Indonesian children.

MSC:

62P10	Applications of statistics to biology and medical sciences; meta analysis
62J05	Linear regression; mixed models

Keywords:

bootstrap; logistic models; repeated measures; longitudinal data; generalized linear models; xerophthalmia