AssignTreatment: Assign treatment based on true propensity score model
In kaz-yos/distributed: Examine Privacy Preserving Data Analysis Methods in Simulated Distributed Data Network
Description
Usage
Arguments
Value
Author(s)
View source: R/01.GenerateData.R
Description
A binary treatment is assigned as a Bernoulli(p_i) random variable where
p_i is an individual-specific treatment probability (true propensity score)
calculated from covariate values and coefficients.
Usage
1
AssignTreatment(dfX, alpha0, alphaX)
Arguments
dfX
data frame including covariates
alpha0
a scalar value coeffcient for the intercept
alphaX
a vector of length 7 specifiying true coefficients for 7 covariates
Value
data frame with additional true propensity score pA and treatment A.
Author(s)
Kazuki Yoshida
kaz-yos/distributed documentation built on May 27, 2019, 4:50 a.m.
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Description Usage Arguments Value Author(s)
View source: R/01.GenerateData.R
Description
A binary treatment is assigned as a Bernoulli(p_i) random variable where p_i is an individual-specific treatment probability (true propensity score) calculated from covariate values and coefficients.
Usage
1 | AssignTreatment(dfX, alpha0, alphaX)
|
Arguments
dfX |
data frame including covariates |
alpha0 |
a scalar value coeffcient for the intercept |
alphaX |
a vector of length 7 specifiying true coefficients for 7 covariates |
Value
data frame with additional true propensity score pA and treatment A.
Author(s)
Kazuki Yoshida
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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