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Journals / Mugla Journal of Science and Technology / 2016 / Cilt: 0 Sayı: 0

LINEAR REGRESSION MODEL ESTİMATİON FOR RIGHT CENSORED DATA

Ersin Yılmaz
Dursun Aydın
Pages
21–22
Publication Date
2016-05-26
DOI
—
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AI Summary & Key Takeaways

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

This study also might be useful for the health studies because of the censored data used in medical issues generally.

📌 3 Key Takeaways

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Objective & Hypothesis:In this study, firstly we will define a right censored data.
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Key Findings & Data:If we say shortly right-censored data is censoring values that above the exact line.
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Conclusion & Impact:This study also might be useful for the health studies because of the censored data used in medical issues generally.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

In this study, firstly we will define a right censored data. If we say shortly right-censored data is censoring values that above the exact line. This may be related with scaling device. And then we will use response variable acquainted from right-censored explanatory variables. Then the linear regression model will be estimated. For censored data’s existence, Kaplan-Meier weights will be used for the estimation of the model. With the weights regression model will be consistent and unbiased with that. And also there is a method for the censored data that is a semi parametric regression and this method also give useful results for censored data too. This study also might be useful for the health studies because of the censored data used in medical issues generally.

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Cite This Article

Yılmaz, E., Aydın, D. (2016). LINEAR REGRESSION MODEL ESTİMATİON FOR RIGHT CENSORED DATA. Mugla Journal of Science and Technology, Cilt: 0 Sayı: 0, 21–22. https://ajindex.com/articles/692132

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References (8)

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