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Taylor Series for Survival Function Approximation using Doubly Censoring with Covariates |
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PP: 353-360 |
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Author(s) |
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Bader A. Aljawadi,
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Abstract |
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| In many real epidemiology or clinical trials, doubly censoring is a common practice. Where the generated data sets may
result in right or left censored failure times along with complete times. In this article, the nonparametric maximum likelihood estimation
technique for approximating the survival function when some covariates are involved under doubly censoring scheme is employed. The
Taylor series is used to extract the baseline hazard function in the Cox model and hence the likelihood ratio test is also used to determine
the appropriate order for Taylor series. This analytical approach demonstrates by a simulation study followed by a real case study using
HIV data set. |
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