The Accelerated Failure Time Model Under Biased Sampling

Micha Mandel; Ya'akov Ritov

doi:10.1111/j.1541-0420.2009.01366_1.x

The Accelerated Failure Time Model Under Biased Sampling

Micha Mandel^*
, Ya'akov Ritov

^*Corresponding author for this work

Department of Statistics

Research output: Contribution to journal › Article › peer-review

21 Scopus citations

Abstract

Chen (2009, Biometrics) studies the semi-parametric accelerated failure time model for data that are size biased. Chen considers only the uncensored case and uses hazard-based estimation methods originally developed for censored observations. However, for uncensored data, a simple linear regression on the log scale is more natural and provides better estimators.

Original language	English
Pages (from-to)	1306-1308
Number of pages	3
Journal	Biometrics
Volume	66
Issue number	4
DOIs	https://doi.org/10.1111/j.1541-0420.2009.01366_1.x
State	Published - Dec 2010

Keywords

Length bias
Size bias
Survival
Weighted distribution

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10.1111/j.1541-0420.2009.01366_1.x

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title = "The Accelerated Failure Time Model Under Biased Sampling",

abstract = "Chen (2009, Biometrics) studies the semi-parametric accelerated failure time model for data that are size biased. Chen considers only the uncensored case and uses hazard-based estimation methods originally developed for censored observations. However, for uncensored data, a simple linear regression on the log scale is more natural and provides better estimators.",

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KW - Length bias

KW - Size bias

KW - Survival

KW - Weighted distribution

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The Accelerated Failure Time Model Under Biased Sampling

Abstract

Keywords

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