Abstract
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 single 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.
Original language | English (US) |
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Pages (from-to) | 381-394 |
Number of pages | 14 |
Journal | Biometrics |
Volume | 45 |
Issue number | 2 |
DOIs | |
State | Published - 1989 |
Externally published | Yes |
ASJC Scopus subject areas
- Statistics and Probability
- General Biochemistry, Genetics and Molecular Biology
- General Immunology and Microbiology
- General Agricultural and Biological Sciences
- Applied Mathematics