Estimate outcome predictions — OutPred • PDRobust

Fits the outcome mean model and predicts each row of pred_dat under treatment a and survival status 1. The model is fitted again each time the function is called.

Usage

OutPred(out_fo, fit_dat, pred_dat, a, mapping, ...)

Arguments

out_fo: outcome mean model formula
fit_dat: A data frame containing the observations used to fit the outcome mean model.
pred_dat: A data frame containing the observations for which outcome predictions are requested.
a: The treatment level under which outcomes are predicted, either 0 or 1.
mapping: A pd_mapping object. Its outcome type determines whether the function uses linear regression or logistic regression.
...: Additional arguments passed to stats::lm() or stats::glm().

Value

A numeric vector of predicted outcome means, one for each row of pred_dat, rounded to three decimal places.

Examples

data("BiSample", package = "PDRobust")
map <- Mapping(
  id = "id", time = "time", treatment = "A",
  survival = "S", outcome = "Y",
  baseline_time = 0, cutoff_time = 2,
  covariates = c("X1", "X2", "X4"),
  interest_vars = c("X1", "X2"), y_type = "B"
)
pd_dat <- DataStandard(BiSample, map)
mu1 <- OutPred(Y ~ X1 + X2 + A + S, pd_dat, pd_dat, a = 1, mapping = map)
head(mu1)
#> [1] 0.230 0.230 0.230 0.222 0.222 0.222