Double Robustness in Estimation of Causal Treatment Effects
Double Robustness in Estimation of Causal Treatment Effects
Double Robustness in Estimation of Causal Treatment Effects
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7. Discussion<br />
• Regression model<strong>in</strong>g and <strong>in</strong>verse propensity score weight<strong>in</strong>g are two<br />
popular approaches when one is will<strong>in</strong>g to assume no unmeasured<br />
confounders<br />
• The double robust estimator comb<strong>in</strong>es both and <strong>of</strong>fers protection<br />
aga<strong>in</strong>st mismodel<strong>in</strong>g<br />
• Offers ga<strong>in</strong>s <strong>in</strong> precision <strong>of</strong> estimation over simple <strong>in</strong>verse weight<strong>in</strong>g<br />
• May not be as precise as regression model<strong>in</strong>g when the regression is<br />
correctly modeled, but adds protection, and modifications are<br />
available<br />
• Doubly robust estimators are also available for more complicated<br />
problems<br />
<strong>Double</strong> <strong>Robustness</strong>, EPID 369, Spr<strong>in</strong>g 2007 42
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