### Abstract

Overadjustment is defined inconsistently. This term is meant to describe control (eg, by regression adjustment, stratification, or restriction) for a variable that either increases net bias or decreases precision without affecting bias. We define overadjust-ment bias as control for an intermediate variable (or a descending proxy for an intermediate variable) on a causal path from exposure to outcome. We define unnecessary adjustment as control for a variable that does not affect bias of the causal relation between exposure and outcome but may affect its precision. We use causal diagrams and an empirical example (the effect of maternal smoking on neonatal mortality) to illustrate and clarify the definition of overadjustment bias, and to distinguish overadjustment bias from unnecessary adjustment. Using simulations, we quantify the amount of bias associated with overadjustment. Moreover, we show that this bias is based on a different causal structure from confounding or selection biases. Overadjustment bias is not a finite sample bias, while inefficiencies due to control for unnecessary variables are a function of sample size.

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

Pages (from-to) | 488-495 |

Number of pages | 8 |

Journal | Epidemiology |

Volume | 20 |

Issue number | 4 |

DOIs | |

State | Published - Jul 2009 |

Externally published | Yes |

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### ASJC Scopus subject areas

- Epidemiology

### Cite this

*Epidemiology*,

*20*(4), 488-495. https://doi.org/10.1097/EDE.0b013e3181a819a1

**Overadjustment bias and unnecessary adjustment in epidemiologic studies.** / Schisterman, Enrique F.; Cole, Stephen R.; Platf, Robert W.

Research output: Contribution to journal › Article

*Epidemiology*, vol. 20, no. 4, pp. 488-495. https://doi.org/10.1097/EDE.0b013e3181a819a1

}

TY - JOUR

T1 - Overadjustment bias and unnecessary adjustment in epidemiologic studies

AU - Schisterman, Enrique F.

AU - Cole, Stephen R.

AU - Platf, Robert W.

PY - 2009/7

Y1 - 2009/7

N2 - Overadjustment is defined inconsistently. This term is meant to describe control (eg, by regression adjustment, stratification, or restriction) for a variable that either increases net bias or decreases precision without affecting bias. We define overadjust-ment bias as control for an intermediate variable (or a descending proxy for an intermediate variable) on a causal path from exposure to outcome. We define unnecessary adjustment as control for a variable that does not affect bias of the causal relation between exposure and outcome but may affect its precision. We use causal diagrams and an empirical example (the effect of maternal smoking on neonatal mortality) to illustrate and clarify the definition of overadjustment bias, and to distinguish overadjustment bias from unnecessary adjustment. Using simulations, we quantify the amount of bias associated with overadjustment. Moreover, we show that this bias is based on a different causal structure from confounding or selection biases. Overadjustment bias is not a finite sample bias, while inefficiencies due to control for unnecessary variables are a function of sample size.

AB - Overadjustment is defined inconsistently. This term is meant to describe control (eg, by regression adjustment, stratification, or restriction) for a variable that either increases net bias or decreases precision without affecting bias. We define overadjust-ment bias as control for an intermediate variable (or a descending proxy for an intermediate variable) on a causal path from exposure to outcome. We define unnecessary adjustment as control for a variable that does not affect bias of the causal relation between exposure and outcome but may affect its precision. We use causal diagrams and an empirical example (the effect of maternal smoking on neonatal mortality) to illustrate and clarify the definition of overadjustment bias, and to distinguish overadjustment bias from unnecessary adjustment. Using simulations, we quantify the amount of bias associated with overadjustment. Moreover, we show that this bias is based on a different causal structure from confounding or selection biases. Overadjustment bias is not a finite sample bias, while inefficiencies due to control for unnecessary variables are a function of sample size.

UR - http://www.scopus.com/inward/record.url?scp=67651021231&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=67651021231&partnerID=8YFLogxK

U2 - 10.1097/EDE.0b013e3181a819a1

DO - 10.1097/EDE.0b013e3181a819a1

M3 - Article

VL - 20

SP - 488

EP - 495

JO - Epidemiology

JF - Epidemiology

SN - 1044-3983

IS - 4

ER -