summary: Summary of the average treatment effects from AIPW
In AIPW: Augmented Inverse Probability Weighting
Description
Arguments
Value
R6 Usage
See Also
Description
Calculate average causal effects in RD, RR and OR in the fitted AIPW or AIPW_tmle object using the estimated efficient influence functions
Arguments
g.bound
Value between [0,1] at which the propensity score should be truncated.
Propensity score will be truncated to [g.bound, 1-g.bound] when one g.bound value is provided, or to [min(g.bound), max(g.bound)] when two values are provided.
Defaults to 0.025.
Value
estimates and result (public variables): Risks, Average treatment effect in RD, RR and OR.
R6 Usage
$summary(g.bound = 0.025)
$summary(g.bound = c(0.025,0.975))
See Also
AIPW and AIPW_tmle
AIPW documentation built on June 11, 2021, 5:08 p.m.
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Description Arguments Value R6 Usage See Also
Description
Calculate average causal effects in RD, RR and OR in the fitted AIPW or AIPW_tmle object using the estimated efficient influence functions
Arguments
g.bound |
Value between [0,1] at which the propensity score should be truncated. Propensity score will be truncated to [g.bound, 1-g.bound] when one g.bound value is provided, or to [min(g.bound), max(g.bound)] when two values are provided. Defaults to 0.025. |
Value
estimates and result (public variables): Risks, Average treatment effect in RD, RR and OR.
R6 Usage
$summary(g.bound = 0.025)
$summary(g.bound = c(0.025,0.975))
See Also
AIPW and AIPW_tmle
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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