MODEL KOZIOL-GREEN UNTUK ESTIMASI FUNGSI SURVIVAL PADA OBSERVASI TERSENSOR KANAN
Survival data analysis refers to some statistical methods to analyze time-toevent data. The analysis often discuss about observation unit�s probability of survive, known as survival function. Survival function can be estimated using nonparametric method. Two well-known estimators to estimate survi...
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| 格式: | Theses and Dissertations NonPeerReviewed |
| 出版: |
[Yogyakarta] : Universitas Gadjah Mada
2014
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| 在線閱讀: | https://repository.ugm.ac.id/133337/ http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=73949 |
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| 總結: | Survival data analysis refers to some statistical methods to analyze time-toevent
data. The analysis often discuss about observation unit�s probability of survive,
known as survival function. Survival function can be estimated using nonparametric
method. Two well-known estimators to estimate survival function are Kaplan-Meier
and Nelson-Aalen.
Right censored observations usually found in time-to-event data. Kaplan-
Meier and Nelson-Aalen estimator assume that the survival function on the censored
time equal to survival function on the time before. Therefore, the estimation of
survival function on the censored time is less precise. That problem can be solved
with alternate survival function estimator. That is using Koziol-Green Model. The
advantage of this alternate estimator is the survival function on the censored time not
assumed equal to survival function on the time before, but have its own estimation.
Also the calculating method for the alternate estimator is much simple. We only need
calculate the proportion of uncensored data and the empirical cumulative probability
to estimate the survival function. |
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