Lucy D’Agostino McGowan

Wake Forest University

- Adjusting for baseline covariates can make an estimate
*more efficient* - Propensity score weighting is
*more efficient*that direct adjustment - Sometimes we are
*more comfortable with the functional form of the propensity score*(predicting exposure) than the outcome model

**simulated**data (100 observations)

- Treatment is
**randomly**assigned - There are
**two baseline covariates**:`age`

and`weight`

**True average treatment effect**: 1

Characteristic |
Beta |
SE^{1} |
95% CI^{1} |
p-value |
---|---|---|---|---|

treatment | 0.93 | 0.803 | -0.66, 2.5 | 0.2 |

^{1} SE = Standard Error, CI = Confidence Interval |

Characteristic |
Beta |
SE^{1} |
95% CI^{1} |
p-value |
---|---|---|---|---|

treatment | 1.0 | 0.204 | 0.59, 1.4 | <0.001 |

weight | 0.34 | 0.106 | 0.13, 0.55 | 0.002 |

age | 0.20 | 0.005 | 0.19, 0.22 | <0.001 |

^{1} SE = Standard Error, CI = Confidence Interval |

Characteristic | Beta | SE | 95% CI | p-value |
---|---|---|---|---|

treatment | 1 | 0.202 | 0.6, 1.4 | <0.001 |

**simulated**data (10,000 observations)

- Treatment is
**randomly**assigned - There are
**two baseline covariates**:`age`

and`weight`

Characteristic |
Beta |
SE^{1} |
95% CI^{1} |
p-value |
---|---|---|---|---|

treatment | 0.96 | 0.083 | 0.80, 1.1 | <0.001 |

^{1} SE = Standard Error, CI = Confidence Interval |

Characteristic |
Beta |
SE^{1} |
95% CI^{1} |
p-value |
---|---|---|---|---|

treatment | 1.0 | 0.020 | 0.98, 1.1 | <0.001 |

weight | 0.20 | 0.010 | 0.18, 0.22 | <0.001 |

age | 0.20 | 0.000 | 0.20, 0.20 | <0.001 |

^{1} SE = Standard Error, CI = Confidence Interval |

Characteristic | Beta | SE | 95% CI | p-value |
---|---|---|---|---|

treatment | 1 | 0.02 | 1, 1.1 | <0.001 |

**simulated**data (10,000 observations)

- Treatment is
**not**randomly assigned - There are
**two baseline confounders**:`age`

and`weight`

- The treatment effect is
**homogeneous**

**True average treatment effect**: 1

Characteristic |
Beta |
SE^{1} |
95% CI^{1} |
p-value |
---|---|---|---|---|

treatment | 1.8 | 0.085 | 1.7, 2.0 | <0.001 |

^{1} SE = Standard Error, CI = Confidence Interval |

Characteristic |
Beta |
SE^{1} |
95% CI^{1} |
p-value |
---|---|---|---|---|

treatment | 0.98 | 0.021 | 0.94, 1.0 | <0.001 |

weight | 0.20 | 0.010 | 0.18, 0.22 | <0.001 |

age | 0.20 | 0.000 | 0.20, 0.20 | <0.001 |

^{1} SE = Standard Error, CI = Confidence Interval |

Characteristic | Beta | SE | 95% CI | p-value |
---|---|---|---|---|

treatment | 1 | 0.022 | 0.9, 1 | <0.001 |