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|
# classes: .glimML
## TODO add ci_method later?
#################### .glimML ------
#' @title Parameters from special models
#' @name model_parameters.glimML
#'
#' @description
#' Parameters from special regression models not listed under one of the
#' previous categories yet.
#'
#' @param component Model component for which parameters should be shown. May be
#' one of `"conditional"`, `"precision"` (e.g. **betareg**), `"scale"` (e.g.
#' **ordinal**), `"extra"` (e.g. **glmx**), `"marginal"` (e.g. **mfx**),
#' `"conditional"` or `"full"` (for `MuMIn::model.avg()`) or `"all"`. See section
#' _Model components_ for an overview of possible options for `component`.
#' @inheritParams model_parameters.default
#' @inheritParams model_parameters.brmsfit
#' @inheritParams simulate_model
#'
#' @seealso [insight::standardize_names()] to rename columns into a consistent,
#' standardized naming scheme.
#'
#' @inheritSection model_parameters.zcpglm Model components
#'
#' @examples
#' library(parameters)
#' if (require("brglm2", quietly = TRUE)) {
#' data("stemcell")
#' model <- bracl(
#' research ~ as.numeric(religion) + gender,
#' weights = frequency,
#' data = stemcell,
#' type = "ML"
#' )
#' model_parameters(model)
#' }
#' @return A data frame of indices related to the model's parameters.
#' @export
model_parameters.glimML <- function(model,
ci = 0.95,
bootstrap = FALSE,
iterations = 1000,
component = "conditional",
standardize = NULL,
exponentiate = FALSE,
p_adjust = NULL,
include_info = getOption("parameters_info", FALSE),
keep = NULL,
drop = NULL,
verbose = TRUE,
...) {
component <- insight::validate_argument(
component,
c("conditional", "random", "dispersion", "all")
)
if (component == "all") {
merge_by <- c("Parameter", "Component")
} else {
merge_by <- "Parameter"
}
# dispersion is just an alias...
if (component == "dispersion") {
component <- "random"
}
out <- .model_parameters_generic(
model = model,
ci = ci,
component = component,
bootstrap = bootstrap,
iterations = iterations,
merge_by = "Parameter",
standardize = standardize,
exponentiate = exponentiate,
p_adjust = p_adjust,
keep_parameters = keep,
drop_parameters = drop,
include_info = include_info,
verbose = verbose,
...
)
attr(out, "object_name") <- insight::safe_deparse_symbol(substitute(model))
out
}
#' @export
standard_error.glimML <- function(model, ...) {
insight::check_if_installed("aod")
s <- methods::slot(aod::summary(model), "Coef")
se <- s[, 2]
.data_frame(
Parameter = .remove_backticks_from_string(rownames(s)),
SE = as.vector(se)
)
}
#' @export
p_value.glimML <- function(model, ...) {
insight::check_if_installed("aod")
s <- methods::slot(aod::summary(model), "Coef")
p <- s[, 4]
.data_frame(
Parameter = .remove_backticks_from_string(rownames(s)),
p = as.vector(p)
)
}
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