Nothing
DATA <- RobinCar:::data_sim
DATA$A <- as.factor(DATA$A)
DATA$y <- ifelse(DATA$y > 2, 1, 0)
test_that("test calibration", {
this <- suppressWarnings(robincar_glm(
df=DATA,
response_col="y",
treat_col="A",
car_strata_cols=c("z1"),
car_scheme="biased-coin",
g_family=binomial(link="logit"),
g_accuracy=7,
formula="y ~ A + x3"))
that <- Robin_g(
robin.data=DATA,
car.scheme="stratified_biased_coin",
car.z=c("z1"),
robin.x=c("x3"),
robin.x_to_include_z=FALSE,
robin.g_family=binomial(link="logit"),
robin.g_accuracy=7,
robin.formula=NULL,
robin.adj_method="homogeneous"
)
for(joint in c(FALSE, TRUE)){
for(add_x in c("x3", NULL)){
calib_this <- suppressWarnings(robincar_calibrate(
result=this,
joint=joint,
add_x=add_x
))
calib_that <- Robin_calibrate(
robin.g_object=that$robin.g_object,
robin.add_x=add_x,
robin.add_x_to_include_z=joint,
robin.vcovHC="HC0"
)
calib_this_est <- calib_this$result$estimate
calib_this_se <- calib_this$result$se
calib_this_vc <- calib_this$varcov
dimnames(calib_this_vc) <- NULL
calib_that_vc <- calib_that$varcov
dimnames(calib_that_vc) <- NULL
names(calib_this_est) <- NULL
names(calib_this_se) <- NULL
expect_equal(calib_this_est, calib_that$estimation$estimate)
# NEW: variance will no longer be the same now that we have done
# the finite sample correction for the variance estimation
# when there are lots of 0's in the response vector
# expect_equal(calib_this_se, calib_that$estimation$se)
# expect_equal(calib_this_vc, calib_that_vc)
}
}
})
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