Estimation of the Cox model with grouped lifetimes

This paper presents how random numbers can be used to transform grouped lifetimes into a pseudo-complete sample. The aim of the study is to investigate the Fisher consistency of the partial likelihood estimator of the regression parameters in the Cox model based on the restored sample. It has been proven that for elliptical-type distributional assumptions about explanatory variables the estimators of the regression parameters in the Cox model based on the pseudo-complete sample are consistent up to a scaling factor. A simulation study illustrates the asymptotic properties of the estimates. In addition, real data case analysis is presented.

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Publication Details

Journal
Statistics in Transition New Series
Published
2024-12-11
DOI
https://doi.org/10.59139/stattrans-2024-009
Primary Topic
Theoretical and Computational Physics
Type
article
Field-Weighted Citation Impact
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article

Estimation of the Cox model with grouped lifetimes

Piotr Nowak
Statistics in Transition New Series
Theoretical and Computational Physics
article

Estimation of the Cox model with grouped lifetimes

Piotr Nowak
article en

Abstract

This paper presents how random numbers can be used to transform grouped lifetimes into a pseudo-complete sample. The aim of the study is to investigate the Fisher consistency of the partial likelihood estimator of the regression parameters in the Cox model based on the restored sample. It has been proven that for elliptical-type distributional assumptions about explanatory variables the estimators of the regression parameters in the Cox model based on the pseudo-complete sample are consistent up to a scaling factor. A simulation study illustrates the asymptotic properties of the estimates. In addition, real data case analysis is presented.

Statistics in Transition New SeriesVol. 25(4)
Openalex Percentile: Top 86%
Theoretical and Computational Physics
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Estimation of the Cox model with grouped lifetimes — Piotr Nowak · Statistics in Transition New Series (2024) | TGRS Research Map | TGRS