Article Per Year (5 Year)
p-Index From 2020 - 2025
0
P-Index
This Author published in this journals
All Journal Journal of Fundamental Mathematics and Applications (JFMA)
Rianti Siswi Utami
Departemen Matematika, Universitas Gadjah Mada, Yogyakarta
Decision Sciences, Operations Research & Management

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
METODE MULTIPLE IMPUTATION UNTUK MENGATASI KOVARIAT TAK LENGKAP PADA DATA KEJADIAN BERULANG Rianti Siswi Utami; Danardono Danardono
Journal of Fundamental Mathematics and Applications (JFMA) Vol 2, No 2 (2019)
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (391.475 KB) | DOI: 10.14710/jfma.v2i2.36

Abstract

Multiple imputation is one of estimation method used to impute missing observations. This method imputes missing observation several times then it is more possible to get the right estimate than just one time imputation. In this research, the method will be applied to estimate missing observations in covariates of recurrent event data. Some multiple imputation methods will be considered including combination of the event indicator, the event  times,   the logarithm of event times, and the cumulative baseline hazard. To compare these methods, Monte Carlo simulation will be used based on relative bias and Mean Squared Error (MSE). The recurrent events will be modelled using Cox proportional hazard model. Furthermore, real data application will be presented.
Co-Authors Danardono Danardono