Adjust doc to prevent gbm warning with multinomial

R/get_w_from_ps.R

@@ -199,22 +199,27 @@
 #'                     estimand = "ATT", treated = "A")
 #' all.equal(w1, w3)
 #'
-#' #Using MMWS
+#' # Using MMWS
 #' w4 <- get_w_from_ps(ps, treat = lalonde$treat,
 #'                     estimand = "ATE", subclass = 20,
 #'                     stabilize = TRUE)
-#' @examplesIf requireNamespace("gbm", quietly = TRUE)
-#' #A multi-category example using GBM predicted probabilities
-#' library(gbm)
-#' T3 <- factor(sample(c("A", "B", "C"), nrow(lalonde), replace = TRUE))
-#'
-#' gbm.fit <- gbm(T3 ~ age + educ + race + married +
-#'                  nodegree + re74 + re75, data = lalonde,
-#'                distribution = "multinomial", n.trees = 200,
-#'                interaction.depth = 3)
-#' ps.multi <- drop(predict(gbm.fit, type = "response",
-#'                          n.trees = 200))
-#' w <- get_w_from_ps(ps.multi, T3, estimand = "ATE")
+#'
+#' # A multi-category example using predicted probabilities
+#' # from multinomial logistic regression
+#' T3 <- factor(sample(c("A", "B", "C"), nrow(lalonde),
+#'                     replace = TRUE))
+#'
+#' multi.fit <- multinom_weightit(
+#'   T3 ~ age + educ + race + married +
+#'     nodegree + re74 + re75, data = lalonde,
+#'   vcov = "none"
+#' )
+#'
+#' ps.multi <- fitted(multi.fit)
+#' head(ps.multi)
+#'
+#' w5 <- get_w_from_ps(ps.multi, treat = T3,
+#'                     estimand = "ATE")
 
 #' @export
 get_w_from_ps <- function(ps, treat, estimand = "ATE", focal = NULL, treated = NULL,