trim_pop: Subset Population so Population Covariates are within bounds...
In benjamin-ackerman/generalize: Generalizing Average Treatment Effects from RCTs to Target Populations
Description
Usage
Arguments
Value
Description
Subset Population so Population Covariates are within bounds of Trial Covariates
Usage
1
Arguments
trial
variable name denoting binary trial participation (1 = trial participant, 0 = not trial participant)
selection_covariates
vector of covariate names in data set that predict trial participation
data
data frame comprised of "stacked" trial and target population data
Value
trim_pop returns a data frame, where the target population covariates do not exceed the bounds of the trial covariates
benjamin-ackerman/generalize documentation built on Oct. 11, 2020, 3:58 a.m.
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Description Usage Arguments Value
Description
Subset Population so Population Covariates are within bounds of Trial Covariates
Usage
1 |
Arguments
trial |
variable name denoting binary trial participation (1 = trial participant, 0 = not trial participant) |
selection_covariates |
vector of covariate names in data set that predict trial participation |
data |
data frame comprised of "stacked" trial and target population data |
Value
trim_pop returns a data frame, where the target population covariates do not exceed the bounds of the trial covariates
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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