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 .; Aunuddin .; Khairil Anwar Notodiputro; I Gusti Putu Purnaba

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

Abstract

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