KAJIAN SIMULASI KETAKNORMALAN PENGARUH ACAK DAN BANYAKNYA DERET DATA LONGITUDINAL DALAM PEMODELAN BERSAMA (JOINT MODELING) (Simulation Study of Random Effects Nonnormality and Number of Longitudinal Data Series in Joint Modeling)
| Main Authors: | ., Indahwati; Departemen Statistika FMIPA – IPB, ., Aunuddin; Departemen Statistika FMIPA – IPB, Notodiputro, Khairil Anwar; Departemen Statistika FMIPA – IPB, Purnaba, I Gusti Putu; Departemen Matematika, FMIPA IPB |
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| Format: | Article info application/pdf eJournal |
| Bahasa: | eng |
| Terbitan: |
FORUM STATISTIKA DAN KOMPUTASI
, 2011
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| Online Access: |
http://journal.ipb.ac.id/index.php/statistika/article/view/4919 http://journal.ipb.ac.id/index.php/statistika/article/view/4919/3351 |
Daftar Isi:
- Joint modeling is intended to model longitudinal response process that affect the other primary response based on assumption that both processes induced by the same random effects. One of the assumptions that must be met in joint modeling is normality of random effects and intra-subject error. The simulation results show that the robustness of parameter estimates of joint model to the assumption of random effects normality can be achieved by increasing the frequency of longitudinal observations. Keywords: longitudinal data, joint modeling, robust