Nothing
## ---- include = FALSE---------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "../man/figures/README-"
)
load("../data/star.rda")
## ----sample_split, warning = FALSE, message = FALSE---------------------------
library(dplyr)
library(evalITR)
# specifying the outcome
outcomes <- "g3tlangss"
# specifying the treatment
treatment <- "treatment"
# specifying the data (remove other outcomes)
star_data <- star %>% dplyr::select(-c(g3treadss,g3tmathss))
# specifying the formula
user_formula <- as.formula(
"g3tlangss ~ treatment + gender + race + birthmonth +
birthyear + SCHLURBN + GRDRANGE + GKENRMNT + GKFRLNCH +
GKBUSED + GKWHITE ")
# estimate ITR
fit <- estimate_itr(
treatment = treatment,
form = user_formula,
data = star_data,
algorithms = c("causal_forest"),
budget = 0.2,
split_ratio = 0.7)
# evaluate ITR
est <- evaluate_itr(fit)
## ----sp_summary---------------------------------------------------------------
# summarize estimates
summary(est)
## ----est_extract, warning = FALSE, message = FALSE, fig.width = 6, fig.height = 4----
# plot GATE estimates
library(ggplot2)
gate_est <- summary(est)$GATE
plot_estimate(gate_est, type = "GATE") +
scale_color_manual(values = c("#0072B2", "#D55E00"))
## ----sp_plot, fig.width = 6, fig.height = 4-----------------------------------
# plot the AUPEC
plot(est)
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