Binary geometric process model for the modeling of longitudinal binary data with trend
β Scribed by Jennifer S. K. Chan; Doris Y. P. Leung
- Book ID
- 105855347
- Publisher
- Springer
- Year
- 2010
- Tongue
- English
- Weight
- 800 KB
- Volume
- 25
- Category
- Article
- ISSN
- 0943-4062
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## Abstract Generalized linear models with random effects and/or serial dependence are commonly used to analyze longitudinal data. However, the computation and interpretation of marginal covariate effects can be difficult. This led Heagerty (1999, 2002) to propose models for longitudinal binary dat
We propose an alternative to the method of generalized estimating equations (GEE) for inference about binary longitudinal data. Unlike GEE, the method is practicable when the data consist of long time series on each subject and the set of observation times is not necessarily common to all subjects.