Correcting for exposure misclassification using survival analysis with a time-varying exposure

Ann Epidemiol. 2012 Nov;22(11):799-806. doi: 10.1016/j.annepidem.2012.09.003. Epub 2012 Oct 5.


Purpose: Survival analysis is increasingly being used in perinatal epidemiology to assess time-varying risk factors for various pregnancy outcomes. Here we show how quantitative correction for exposure misclassification can be applied to a Cox regression model with a time-varying dichotomous exposure.

Methods: We evaluated influenza vaccination during pregnancy in relation to preterm birth among 2267 non-malformed infants whose mothers were interviewed as part of the Slone Birth Defects Study during 2006 through 2011. The hazard of preterm birth was modeled using a time-varying exposure Cox regression model with gestational age as the time-scale. The effect of exposure misclassification was then modeled using a probabilistic bias analysis that incorporated vaccination date assignment. The parameters for the bias analysis were derived from both internal and external validation data.

Results: Correction for misclassification of prenatal influenza vaccination resulted in an adjusted hazard ratio (AHR) slightly higher and less precise than the conventional analysis: Bias-corrected AHR 1.04 (95% simulation interval, 0.70-1.52); conventional AHR, 1.00 (95% confidence interval, 0.71-1.41).

Conclusions: Probabilistic bias analysis allows epidemiologists to assess quantitatively the possible confounder-adjusted effect of misclassification of a time-varying exposure, in contrast with a speculative approach to understanding information bias.

Publication types

  • Evaluation Study
  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, Non-P.H.S.
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Bias*
  • Confidence Intervals
  • Female
  • Gestational Age*
  • Humans
  • Infant, Newborn
  • Infant, Premature
  • Influenza Vaccines / administration & dosage*
  • Influenza Vaccines / immunology
  • Influenza, Human / immunology
  • Influenza, Human / prevention & control*
  • Monte Carlo Method
  • Pregnancy
  • Pregnancy Outcome / epidemiology*
  • Premature Birth / classification
  • Premature Birth / epidemiology*
  • Proportional Hazards Models
  • Regression Analysis
  • Risk Factors
  • Survival Analysis
  • Time Factors
  • Vaccination / statistics & numerical data


  • Influenza Vaccines