Nothing
# install.packages("~/Dropbox/R/drtmle",repos=NULL,type="source")
library(drtmle)
library(SuperLearner)
context("Testing edge cases.")
test_that("drtmle executes as expected when only one value of gn", {
set.seed(123456)
n <- 200
W <- data.frame(W1 = runif(n), W2 = rnorm(n))
A <- rbinom(n, 1, plogis(W$W1 - W$W2))
Y <- rnorm(n, W$W1 * W$W2 * A, 2)
# univariate reduction with
# all GLMs + stratify
fit1 <- drtmle(
W = W, A = A, Y = Y,
cvFolds = 1, maxIter = 2,
family = gaussian(),
stratify = TRUE,
glm_Q = "W1 + W2",
glm_g = "1",
glm_Qr = "gn",
glm_gr = "Qn",
guard = c("Q", "g"),
reduction = "univariate"
)
expect_true(is.numeric(fit1$gcomp$est))
expect_true(is.numeric(fit1$tmle$est))
expect_true(is.numeric(fit1$tmle$est))
expect_true(is.numeric(fit1$tmle$cov))
expect_true(is.numeric(fit1$drtmle$est))
expect_true(is.numeric(fit1$drtmle$cov))
expect_true(is.numeric(fit1$aiptw$est))
expect_true(is.numeric(fit1$aiptw$cov))
expect_true(is.numeric(fit1$aiptw_c$est))
expect_true(is.numeric(fit1$aiptw_c$cov))
})
test_that("drtmle executes when glm and SL are specified", {
set.seed(123456)
n <- 200
W <- data.frame(W1 = runif(n), W2 = rnorm(n))
A <- rbinom(n, 1, plogis(W$W1 - W$W2))
Y <- rnorm(n, W$W1 * W$W2 * A, 2)
# univariate reduction with
# all GLMs + stratify
expect_warning(fit1 <- drtmle(
W = W, A = A, Y = Y,
cvFolds = 1, maxIter = 2,
family = gaussian(),
returnModels = TRUE,
stratify = FALSE,
glm_Q = "W1 + W2",
SL_Q = c("SL.glm", "SL.mean"),
glm_g = "1",
SL_g = c("SL.glm", "SL.mean"),
glm_Qr = "gn",
SL_Qr = c("SL.glm", "SL.mean"),
glm_gr = "Qn",
SL_gr = c("SL.glm", "SL.mean"),
guard = c("Q", "g"),
reduction = "univariate"
))
expect_true(is.numeric(fit1$gcomp$est))
expect_true(is.numeric(fit1$tmle$est))
expect_true(is.numeric(fit1$tmle$est))
expect_true(is.numeric(fit1$tmle$cov))
expect_true(is.numeric(fit1$drtmle$est))
expect_true(is.numeric(fit1$drtmle$cov))
expect_true(is.numeric(fit1$aiptw$est))
expect_true(is.numeric(fit1$aiptw$cov))
expect_true(is.numeric(fit1$aiptw_c$est))
expect_true(is.numeric(fit1$aiptw_c$cov))
expect_true(inherits(fit1$QnMod[[1]], "SuperLearner"))
expect_true(inherits(fit1$gnMod[[1]]$A[[1]], "SuperLearner"))
expect_true(inherits(fit1$QrnMod[[1]][[1]], "SuperLearner"))
expect_true(inherits(fit1$grnMod[[1]][[1]]$fm1, "SuperLearner"))
expect_true(inherits(fit1$grnMod[[1]][[1]]$fm2, "SuperLearner"))
})
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