A shared parameter model for longitudinal data analysis / Nesma Mady Mohamed Darwish ; Supervised Ahmed Mahmoud Gad
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TextLanguage: English Publication details: Cairo : Nesma Mady Mohamed Darwish , 2013Description: 65 Leaves ; 25cmOther title: - نموذج معالم مشتركة لتحليل البيانات الطوليه [Added title page title]
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قاعة الرسائل الجامعية - الدور الاول | المكتبة المركزبة الجديدة - جامعة القاهرة | Cai01.03.01.M.Sc.2013.Ne.S (Browse shelf(Opens below)) | Not for loan | 01010110062113000 | |||
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مخـــزن الرســائل الجـــامعية - البدروم | المكتبة المركزبة الجديدة - جامعة القاهرة | Cai01.03.01.M.Sc.2013.Ne.S (Browse shelf(Opens below)) | 62113.CD | Not for loan | 01020110062113000 |
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| Cai01.03.01.M.Sc.2013.Im.P A proposed imputation method for longitudinal data analysis / | Cai01.03.01.M.Sc.2013.Im.P A proposed imputation method for longitudinal data analysis / | Cai01.03.01.M.Sc.2013.Ne.S A shared parameter model for longitudinal data analysis / | Cai01.03.01.M.Sc.2013.Ne.S A shared parameter model for longitudinal data analysis / | Cai01.03.01.M.Sc.2013.Ra.A Accelerated life testing under the family of the exponentiated distributions / | Cai01.03.01.M.Sc.2013.Ra.A Accelerated life testing under the family of the exponentiated distributions / | Cai01.03.01.M.Sc.2013.Re.P Phase II multiple linear profiling with small sample sizes / |
Thesis (M.Sc.) - Cairo University - Faculty of Economics and Political Science - Department of Statistics
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
Issued also as CD
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