TY  - BOOK
AU  - Nesma Mady Mohamed Darwish
AU  - Ahmed Mahmoud Gad , 
TI  - A shared parameter model for longitudinal data analysis / 
PY  - 2013///
CY  - Cairo : 
PB  - Nesma Mady Mohamed Darwish , 
KW  - Dropout missing
KW  - Longitudinal data
KW  - Non-random missing
N1  - Thesis (M.Sc.) - Cairo University - Faculty of Economics and Political Science - Department of Statistics; Issued also as CD
N2  - Longitudinal data with dropout are common in practice. The validity of standard methods for analysis of incomplete data depends on the assumption that the missing data mechanism is ignorable according to Rubin's classification. Incomplete longitudinal data can be modeled using pattern mixture, selection and shared parameter models. Inference about longitudinal data with non-random dropout reguires  incorporating a dropout model in the likelihood function
ER  -