#' @export
get_predictions.glm <- function(model,
data_grid = NULL,
terms = NULL,
ci_level,
type = NULL,
typical = NULL,
vcov = NULL,
vcov_args = NULL,
condition = NULL,
interval = "confidence",
bias_correction = FALSE,
link_inverse = insight::link_inverse(model),
model_info = NULL,
verbose = TRUE,
...) {
# does user want standard errors?
se <- !is.null(ci_level) && !is.na(ci_level) && is.null(vcov)
if (type == "simulate") {
# compute ci, two-ways
if (!is.null(ci_level) && !is.na(ci_level)) {
ci <- (1 + ci_level) / 2
} else {
ci <- 0.975
}
# simulate predictions
.do_simulate(model, terms, ci, interval = interval, ...)
} else {
# for models from "robust"-pkg (glmRob) we need to
# suppress warnings about fake models
prdat <- suppressWarnings(stats::predict.glm(
model,
newdata = data_grid,
type = "link",
se.fit = se,
...
))
# copy predictions
.generic_prediction_data(
model,
data_grid,
link_inverse,
prediction_data = prdat,
se,
ci_level,
typical,
terms,
vcov,
vcov_args,
condition,
interval
)
}
}
#' @export
get_predictions.brglm <- get_predictions.glm
#' @export
get_predictions.negbin <- get_predictions.glm
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