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Sains Malaysiana 46(12)(2017): 2529–2539 http://dx.doi.org/10.17576/jsm-2017-4612-31
Bootstrap Intervals in the Presence of
Left-Truncation, Censoring and Covariates with a Parametric
Distribution (Selang Butstrap dalam Kehadiran Pemangkasan Kiri, Penapisan dan Kovariat
dengan Taburan
Parametrik) THIRUNANTHINI MANOHARAN*,
JAYANTHI
ARASAN,
HABSHAH
MIDI
& MOHD
BAKRI
ADAM Department of Mathematics,
Faculty of Science, Universiti Putra
Malaysia, 43400 UPM Serdang,
Selangor Darul Ehsan, Malaysia Laboratory of Computational
Statistics and Operations Research, Universiti
Putra Malaysia 43400 UPM
Serdang, Selangor Darul Ehsan, Malaysia Received: 29 March
2016/Accepted: 18 April 2017 ABSTRACT Left-truncated and censored
survival data are commonly encountered in medical studies. However,
traditional inferential methods that heavily rely on normality
assumptions often fail when lifetimes of observations in a study
are both truncated and censored. Thus, it is important to develop
alternative inferential procedures that ease the assumptions
of normality and unconventionally relies on the distribution
of data in hand. In this research, a three parameter log-normal
parametric survival model was extended to incorporate left-truncated
and right censored medical data with covariates. Following that,
bootstrap inferential procedures using non-parametric and parametric
bootstrap samples were applied to the parameters of this model.
The performance of the parameter estimates was assessed at various
combinations of truncation and censoring levels via a simulation
study. The recommended bootstrap intervals were applied to a
lung cancer survival data. Keywords: Bootstrap method;
covariate; left-truncation; random censoring ABSTRAK Data
terpangkas kiri
dan tertapis wujud
dalam bidang
perubatan dan kaedah
inferensi tradisi
yang sangat bergantung kepada andaian normal sering kali gagal apabila data tidak lengkap akibat mekanisme terpangkas dan tertapis data. Oleh itu, adalah menjadi
keperluan untuk
mengkaji kaedah selang keyakinan alternatif yang kurang bergantung dengan andaian lazim semata-mata,
sebaliknya bergantung
kepada taburan data yang sedia ada. Dalam kajian ini, model mandiran log-lazim dengan kehadiran kovariat dipertimbangkan untuk data perubatan yang terpangkas kiri dan tertapis. Seterusnya, kesesuaian selang keyakinan butstrap yang berasaskan persampelan parametrik dan bukan parametrik diuji untuk setiap
parameter yang wujud dalam
model mandirian log-lazim
menerusi kajian kebarangkalian liputan. Simulasi data jangka hayat dijalankan
pada pelbagai
kombinasi peratusan data terpangkas dan tertapis. Berikutan hasil kajian
tersebut, kaedah selang keyakinan yang dicadangkan telah diuji dengan data pesakit kanser paru-paru. Kata kunci: Kaedah
butstrap; kovariat;
terpangkas kiri; tertapis rawak REFERENCES Arasan,
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