### Abstract

Consider a study in which the effect of a binary exposure on an outcome operates partly through a binary mediator but measurement of the mediator is nondifferentially misclassified. Suppose that an investigator wishes to estimate the direct and indirect effects of the exposure on the outcome. In this paper, the authors describe a mathematical correspondence between the empirical expressions for the natural direct effect and the effect of exposure among the unexposed standardized by a binary confounder. They then exploit this correspondence to prove that the direction of the bias due to nondifferential measurement error in estimating the natural direct and indirect effects is to overestimate the natural direct effect and underestimate the natural indirect effect.

Original language | English (US) |
---|---|

Pages (from-to) | 555-561 |

Number of pages | 7 |

Journal | American Journal of Epidemiology |

Volume | 176 |

Issue number | 6 |

State | Published - Sep 15 2012 |

Externally published | Yes |

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### ASJC Scopus subject areas

- Epidemiology

### Cite this

*American Journal of Epidemiology*,

*176*(6), 555-561.

**Analytic results on the bias due to nondifferential misclassification of a binary mediator.** / Ogburn, Elizabeth Leigh; VanderWeele, Tyler J.

Research output: Contribution to journal › Article

*American Journal of Epidemiology*, vol. 176, no. 6, pp. 555-561.

}

TY - JOUR

T1 - Analytic results on the bias due to nondifferential misclassification of a binary mediator.

AU - Ogburn, Elizabeth Leigh

AU - VanderWeele, Tyler J.

PY - 2012/9/15

Y1 - 2012/9/15

N2 - Consider a study in which the effect of a binary exposure on an outcome operates partly through a binary mediator but measurement of the mediator is nondifferentially misclassified. Suppose that an investigator wishes to estimate the direct and indirect effects of the exposure on the outcome. In this paper, the authors describe a mathematical correspondence between the empirical expressions for the natural direct effect and the effect of exposure among the unexposed standardized by a binary confounder. They then exploit this correspondence to prove that the direction of the bias due to nondifferential measurement error in estimating the natural direct and indirect effects is to overestimate the natural direct effect and underestimate the natural indirect effect.

AB - Consider a study in which the effect of a binary exposure on an outcome operates partly through a binary mediator but measurement of the mediator is nondifferentially misclassified. Suppose that an investigator wishes to estimate the direct and indirect effects of the exposure on the outcome. In this paper, the authors describe a mathematical correspondence between the empirical expressions for the natural direct effect and the effect of exposure among the unexposed standardized by a binary confounder. They then exploit this correspondence to prove that the direction of the bias due to nondifferential measurement error in estimating the natural direct and indirect effects is to overestimate the natural direct effect and underestimate the natural indirect effect.

UR - http://www.scopus.com/inward/record.url?scp=84871657661&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84871657661&partnerID=8YFLogxK

M3 - Article

C2 - 22930481

AN - SCOPUS:84871657661

VL - 176

SP - 555

EP - 561

JO - American Journal of Epidemiology

JF - American Journal of Epidemiology

SN - 0002-9262

IS - 6

ER -