What question did this study set out to answer?

To analyze how covariate measurement errors impact parameter estimation in failure time regression models.

January 1, 1982Biometrika

Covariate measurement errors and parameter estimation in a failure time regression model

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To analyze how covariate measurement errors impact parameter estimation in failure time regression models.
Analyzed regression models considering covariate measurement errors.
Used statistical techniques to estimate parameters accurately despite errors.
Explored implications of errors on result interpretation.
Identified significant biases in parameter estimates due to covariate measurement errors.
Demonstrated the need for correction methods to enhance accuracy in analyses.
Provided insights into improving model robustness against measurement errors.

Implication

Randomized trial investigates parameters affected by covariate measurement errors in regression models, highlighting statistical implications.

Abstract

Journal Article Covariate measurement errors and parameter estimation in a failure time regression model Get access R. L. PRENTICE R. L. PRENTICE Fred Hutchinson Cancer Research CenterSeattle, Washington, U.S.A. Search for other works by this author on: Oxford Academic Google Scholar Biometrika, Volume 69, Issue 2, August 1982, Pages 331–342, https://doi.org/10.1093/biomet/69.2.331 Published: 01 August 1982

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Cite This Study

Ross L. Prentice (1982) studied this question.

synapsesocial.com/papers/69dec89f40ea065679559765 https://doi.org/10.1093/biomet/69.2.331

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Implication

Randomized trial investigates parameters affected by covariate measurement errors in regression models, highlighting statistical implications.

Covariate measurement errors and parameter estimation in a failure time regression model

Key Points

Implication

Abstract

Discussion

Cite This Study

Covariate measurement errors and parameter estimation in a failure time regression model

Key Points

Implication

Abstract

Discussion

Cite This Study

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