𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Combining models in longitudinal data analysis

✍ Scribed by Song Liu; Yuhong Yang

Publisher
Springer Japan
Year
2010
Tongue
English
Weight
286 KB
Volume
64
Category
Article
ISSN
0020-3157

No coin nor oath required. For personal study only.

πŸ“œ SIMILAR VOLUMES

Dispersion models and longitudinal data
Dispersion models and longitudinal data analysis
✍ Bent JΓΈrgensen; Min Tsao πŸ“‚ Article πŸ“… 1999 πŸ› John Wiley and Sons 🌐 English βš– 168 KB πŸ‘ 2 views

Dispersion models provide a #exible class of non-normal distributions with many potential applications in biostatistics, accommodating a wide range of continuous, discrete and mixed data. Starting with Liang and Zeger's generalized estimating equation method, we review some recent applications of di

Residuals analysis of the generalized li
Residuals analysis of the generalized linear models for longitudinal data
✍ Yue-Cune Chang πŸ“‚ Article πŸ“… 2000 πŸ› John Wiley and Sons 🌐 English βš– 196 KB πŸ‘ 3 views

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

Longitudinal data analysis: non-stationa
Longitudinal data analysis: non-stationary error structures and antedependent models
✍ NΓΊΓ±ez-AntΓ³n, Vicente πŸ“‚ Article πŸ“… 1997 πŸ› John Wiley and Sons 🌐 English βš– 101 KB πŸ‘ 2 views

Non-stationary covariance structures had not been analyzed in detail for longitudinal data mainly because the existing applications did not require their use. Data from the Iowa Cochlear Implant Project showed this type of structure and the problem needed to be addressed. We propose a linear model f