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)

Indahwati . (Departemen Statistika FMIPA – IPB)
Aunuddin . (Departemen Statistika FMIPA – IPB)
Khairil Anwar Notodiputro (Departemen Statistika FMIPA – IPB)
I Gusti Putu Purnaba (Departemen Matematika, FMIPA IPB)

FORUM STATISTIKA DAN KOMPUTASI
Vol. 16 No. 2 (2011)

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