# \donttest{
a <- c("A1", "A2")
nodes <- list(c("L1"), c("L2"))
cens <- c("C1", "C2")
y <- "Y"
# mean population outcome
psi_null <- lmtp_tmle(sim_cens, a, y, time_vary = nodes, cens = cens, shift = NULL, folds = 1)
# treatment rule, everyone is increased by 0.5
d <- function(data, x) data[[x]] + 0.5
psi_rule1 <- lmtp_tmle(sim_cens, a, y, time_vary = nodes, cens = cens,
shift = d, folds = 1, mtp = TRUE)
# treatment rule, everyone is decreased by 0.5
d <- function(data, x) data[[x]] - 0.5
psi_rule2 <- lmtp_tmle(sim_cens, a, y, time_vary = nodes, cens = cens,
shift = d, folds = 1, mtp = TRUE)
# Example 1.1
# Additive effect of rule 1 compared to a known constant
lmtp_contrast(psi_rule1, ref = 0.9)
# Example 1.2
# Additive effect of rule 1 compared to the population mean outcome
lmtp_contrast(psi_rule1, ref = psi_null)
# Example 1.3
# Additive effects of rule 1 and 2 compared to the population mean outcome
lmtp_contrast(psi_rule1, psi_rule2, ref = psi_null)
# Example 1.4
# Relative risk of rule 1 compared to observed exposure
lmtp_contrast(psi_rule1, ref = psi_null, type = "rr")
# Example 1.5
# Odds of rule 1 compared to observed exposure
lmtp_contrast(psi_rule1, ref = psi_null, type = "or")
# }
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