Longitudinal studies of cognitive function in Alzheimer's disease (AD) patients are powerful tools to better understand the biology and natural history of the disease, but the attributes of the studies that make them valuable also pose special challenges to analysts. A fundamental problem is the acc
A cautionary note on generalized linear models for covariance of unbalanced longitudinal data
β Scribed by Jianhua Z. Huang; Min Chen; Mehdi Maadooliat; Mohsen Pourahmadi
- Book ID
- 113757563
- Publisher
- Elsevier Science
- Year
- 2012
- Tongue
- English
- Weight
- 319 KB
- Volume
- 142
- Category
- Article
- ISSN
- 0378-3758
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
The generalized estimation equation (GEE) method, one of the generalized linear models for longitudinal data, has been used widely in medical research. However, the related sensitivity analysis problem has not been explored intensively. One of the possible reasons for this was due to the correlated
This paper extends four goodness-of-ΓΏt measures of a generalized linear model (GLM) to random e ects and marginal models for longitudinal data. The four measures are the proportional reduction in entropy measure, the proportional reduction in deviance measure, the concordance correlation coe cient a
Liang and Zeger introduced a class of estimating equations that gives consistent estimates of regression parameters and of their variances in the class of generalized linear models for longitudinal data. When the response variable in such models is subject to overdispersion, the oerdispersion parame