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

Dursun AYDIN; Ersin YILMAZ

doi:https://doi.org/10.18038/estubtda.632694

Article Details

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

Authors:

Dursun AYDIN | Ersin YILMAZ

Publisher:

Eskisehir Technical University

Main Topics:

Astronomy and allied sciences

Journal:

Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering 2019 Vol.20, pp.1-12

Document Type:

Article

Publication Date:

12/2019

Document Language:

English

Document ID (Org No.):

2000416955

pISSN:

2667-4211

DOI:

https://doi.org/10.18038/estubtda.632694

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.

Article Details

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

Authors: Dursun AYDIN | Ersin YILMAZ

Publisher: Eskisehir Technical University

Main Topics: Astronomy and allied sciences

Journal: Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering 2019 Vol.20, pp.1-12

Document Type: Article

Publication Date: 12/2019

Document Language: English

Document ID (Org No.): 2000416955

pISSN: 2667-4211

DOI: https://doi.org/10.18038/estubtda.632694

Issues

Authors:

Dursun AYDIN | Ersin YILMAZ

Publisher:

Eskisehir Technical University

Main Topics:

Astronomy and allied sciences

Journal:

Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering 2019 Vol.20, pp.1-12

Document Type:

Article

Publication Date:

12/2019

Document Language:

English

Document ID (Org No.):

2000416955

pISSN:

2667-4211

DOI:

https://doi.org/10.18038/estubtda.632694