ATEd: Difference in means estimate of the ATE
In zthuang0422/PURM-2021-Latent-Stratification: Maximum Likelihood Latent Stratification
Description
Usage
Arguments
Details
Value
Examples
Description
Computes the ATE by taking the difference in the means.
Usage
1
Arguments
data
data frame containing cols y (positive outcome with zeros) and z (treatment).
Details
For the input data frame, column z is the dummy variable for treatment. If z = 1, then the observation has received treatment.
If z = 0, then the observation has not received treatment.
t.test() from base R can be used as an alternative.
Value
difference in means estimate of the ATE
Examples
1
2
sim = sim_latent_strat(n=10000, piA=0.2, piB=0.1, muA1=5, muA0=4.5, muB1=3, sigma=0.3)
ATEd(sim$data)
zthuang0422/PURM-2021-Latent-Stratification documentation built on Dec. 23, 2021, 10:12 p.m.
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Description Usage Arguments Details Value Examples
Description
Computes the ATE by taking the difference in the means.
Usage
1 |
Arguments
data |
data frame containing cols y (positive outcome with zeros) and z (treatment). |
Details
For the input data frame, column z is the dummy variable for treatment. If z = 1, then the observation has received treatment.
If z = 0, then the observation has not received treatment.
t.test() from base R can be used as an alternative.
Value
difference in means estimate of the ATE
Examples
1 2 | sim = sim_latent_strat(n=10000, piA=0.2, piB=0.1, muA1=5, muA0=4.5, muB1=3, sigma=0.3)
ATEd(sim$data)
|
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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