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Computer program for the proportional hazards measurement error model

T Nakamura1, K Akazawa

  • 1School of Allied Medical Sciences, Nagasaki University, Japan.

Computer Methods and Programs in Biomedicine
|November 1, 1994
PubMed
Summary
This summary is machine-generated.

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Measurement error in covariates biases Cox-regression analysis. This study presents a method and FORTRAN program for asymptotically unbiased parameter estimates, correcting for measurement error in Cox models.

Area of Science:

  • Biostatistics
  • Survival Analysis
  • Statistical Modeling

Background:

  • Cox-regression analysis assumes error-free covariates.
  • Ignoring covariate measurement error leads to biased and misleading results.
  • Bias from measurement error does not decrease with larger sample sizes.

Purpose of the Study:

  • To describe a method for asymptotically unbiased parameter estimation in Cox-regression.
  • To correct for measurement error in covariates within the Cox model.
  • To present a FORTRAN program implementing the correction method.

Main Methods:

  • Utilizes a method for asymptotically unbiased parameter estimation.
  • Corrects for measurement error in covariates.
  • Requires specification of the measurement error distribution (conditional distribution of observed given true values).

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Main Results:

  • Provides asymptotically unbiased estimates of Cox model parameters.
  • Offers a FORTRAN program for implementing the correction method.
  • Obtains asymptotic standard errors for the corrected estimates.

Conclusions:

  • The described method corrects for covariate measurement error in Cox regression.
  • The method does not assume a distribution for the true covariate values.
  • Accommodates tied failure times and independent censoring/loss to follow-up.