pattc_ensemble {DeepLearningCausal} | R Documentation |
PATT_C SL Ensemble
Description
pattc_ensemble
estimates the Population Average Treatment Effect
of the Treated from experimental data with noncompliers
using the super learner ensemble that includes extreme gradient boosting,
glmnet (elastic net regression), random forest and neural nets.
Usage
pattc_ensemble(
response.formula,
exp.data,
pop.data,
treat.var,
compl.var,
compl.SL.learners = c("SL.glmnet", "SL.xgboost", "SL.ranger", "SL.nnet", "SL.glm"),
response.SL.learners = c("SL.glmnet", "SL.xgboost", "SL.ranger", "SL.nnet", "SL.glm"),
ID = NULL,
cluster = NULL,
binary.outcome = FALSE,
bootstrap = FALSE,
nboot = 1000
)
Arguments
response.formula |
formula for the effects of covariates on outcome variable (y ~ x). |
exp.data |
|
pop.data |
|
treat.var |
string for binary treatment variable. |
compl.var |
string for binary compliance variable. |
compl.SL.learners |
vector of names of ML algorithms used for compliance model. |
response.SL.learners |
vector of names of ML algorithms used for response model. |
ID |
string for name of identifier. (currently not used) |
cluster |
string for name of cluster variable. (currently not used) |
binary.outcome |
logical specifying predicted outcome variable will take binary values or proportions. |
bootstrap |
logical for bootstrapped PATT-C. |
nboot |
number of bootstrapped samples. Only used with
|
Value
pattc_ensemble
object of results of t test as PATTC estimate.
Examples
# load datasets
data(exp_data_full) # full experimental data
data(exp_data) #experimental data
data(pop_data) #population data
#attach SuperLearner (model will not recognize learner if package is not loaded)
library(SuperLearner)
set.seed(123456)
#specify models and estimate PATTC
pattc <- pattc_ensemble(response.formula = support_war ~ age + income +
education + employed + job_loss,
exp.data = exp_data_full,
pop.data = pop_data,
treat.var = "strong_leader",
compl.var = "compliance",
compl.SL.learners = c("SL.glm", "SL.nnet"),
response.SL.learners = c("SL.glm", "SL.nnet"),
ID = NULL,
cluster = NULL,
binary.outcome = FALSE)
print(pattc)
pattc_boot <- pattc_ensemble(response.formula = support_war ~ age + income +
education + employed + job_loss,
exp.data = exp_data_full,
pop.data = pop_data,
treat.var = "strong_leader",
compl.var = "compliance",
compl.SL.learners = c("SL.glm", "SL.nnet"),
response.SL.learners = c("SL.glm", "SL.nnet"),
ID = NULL,
cluster = NULL,
binary.outcome = FALSE,
bootstrap = TRUE,
nboot = 1000)
print(pattc_boot)