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Journals / Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering / 2019 / Cilt: 20 - Sayı:

SEMIPARAMETRIC REGRESSION ESTIMATES BASED ON SOME TRANSFORMATION TECHNIQUES FOR RIGHT-CENSORED DATA

Dursun AYDIN
Ersin YILMAZ
Pages
1–12
Publication Date
2019-12-16
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

According to the results of the simulation, it can be said that the Kaplan-Meier weights have been very successful in dealing with censored observations.

📌 3 Key Takeaways

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Objective & Hypothesis:In this paper, we introduce three different data transformation approaches such as synthetic data transformation ([1]; [2]; [3]), Kaplan-Meier weights ([4]; [5] ; [6]) and k-nearest neighbour (kNN) imputation method ([7]) which are commonly used in censored data applications.
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Key Findings & Data:The aforementioned approaches are particularly useful when one deals with censored data.
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Conclusion & Impact:According to the results of the simulation, it can be said that the Kaplan-Meier weights have been very successful in dealing with censored observations.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:right-censored · semi-parametric regression · imputation

Abstract

In this paper, we introduce three different data transformation approaches such as synthetic data transformation ([1]; [2]; [3]), Kaplan-Meier weights ([4]; [5] ; [6]) and k-nearest neighbour (kNN) imputation method ([7]) which are commonly used in censored data applications. The aforementioned approaches are particularly useful when one deals with censored data. The key idea expressed here is to find the smoothing spline estimates for the parametric and nonparametric components of a semiparametric regression model with right-censored data. The estimation is then carried out based on the modified (or transformed) data set obtained via these transformation techniques. In order to compare the outcomes of three approaches in semi-parametric regression setting, we carried out a simulation study. According to the results of the simulation, it can be said that the Kaplan-Meier weights have been very successful in dealing with censored observations.

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Cite This Article

AYDIN, D., YILMAZ, E. (2019). SEMIPARAMETRIC REGRESSION ESTIMATES BASED ON SOME TRANSFORMATION TECHNIQUES FOR RIGHT-CENSORED DATA. Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering, Cilt: 20 - Sayı:, 1–12. https://ajindex.com/articles/196745

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References (1)

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