fit_ipw: Fit IPW weights with a logit propensity score model
In ebenmichael/ents: Maximum Entropy Synthetic Controls
Description
Usage
Arguments
Value
Description
Fit IPW weights with a logit propensity score model
Usage
1
fit_ipw(outcomes, metadata, trt_unit = 1, alpha_w)
Arguments
outcomes
Tidy dataframe with the outcomes and meta data
metadata
Dataframe of metadata
trt_unit
Unit that is treated (target for regression), default: 0
alpha_w
regularization parameter for weights
Value
inverse of predicted propensity scores
outcome regression parameters
control outcomes
treated outcomes
boolean for treated
ebenmichael/ents documentation built on May 31, 2019, 8:45 p.m.
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Description Usage Arguments Value
Description
Fit IPW weights with a logit propensity score model
Usage
1 | fit_ipw(outcomes, metadata, trt_unit = 1, alpha_w)
|
Arguments
outcomes |
Tidy dataframe with the outcomes and meta data |
metadata |
Dataframe of metadata |
trt_unit |
Unit that is treated (target for regression), default: 0 |
alpha_w |
regularization parameter for weights |
Value
inverse of predicted propensity scores outcome regression parameters control outcomes treated outcomes boolean for treated
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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