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# classes: .mlm
#################### .mlm
#' Parameters from multinomial or cumulative link models
#'
#' Parameters from multinomial or cumulative link models
#'
#' @param model A model with multinomial or categorical response value.
#' @inheritParams model_parameters.default
#' @inheritParams simulate_model
#'
#' @details Multinomial or cumulative link models, i.e. models where the
#' response value (dependent variable) is categorical and has more than two
#' levels, usually return coefficients for each response level. Hence, the
#' output from \code{model_parameters()} will split the coefficient tables
#' by the different levels of the model's response.
#'
#' @seealso \code{\link[insight:standardize_names]{standardize_names()}} to rename
#' columns into a consistent, standardized naming scheme.
#'
#' @examples
#' library(parameters)
#' if (require("brglm2")) {
#' 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.
#' @inheritParams simulate_model
#' @importFrom insight get_response
#' @export
model_parameters.mlm <- function(model,
ci = .95,
bootstrap = FALSE,
iterations = 1000,
standardize = NULL,
exponentiate = FALSE,
p_adjust = NULL,
verbose = TRUE,
...) {
out <- .model_parameters_generic(
model = model,
ci = ci,
bootstrap = bootstrap,
iterations = iterations,
merge_by = c("Parameter", "Response"),
standardize = standardize,
exponentiate = exponentiate,
robust = FALSE,
p_adjust = p_adjust,
...
)
attr(out, "object_name") <- deparse(substitute(model), width.cutoff = 500)
out
}
#' @export
standard_error.mlm <- function(model, ...) {
cs <- stats::coef(summary(model))
se <- lapply(names(cs), function(x) {
params <- cs[[x]]
.data_frame(
Parameter = rownames(params),
SE = params[, "Std. Error"],
Response = gsub("^Response (.*)", "\\1", x)
)
})
.remove_backticks_from_parameter_names(do.call(rbind, se))
}
#' @export
p_value.mlm <- function(model, ...) {
cs <- stats::coef(summary(model))
p <- lapply(names(cs), function(x) {
params <- cs[[x]]
.data_frame(
Parameter = rownames(params),
p = params[, "Pr(>|t|)"],
Response = gsub("^Response (.*)", "\\1", x)
)
})
.remove_backticks_from_parameter_names(do.call(rbind, p))
}
#' @export
ci.mlm <- function(x, ci = .95, ...) {
if (is.null(insight::find_weights(x))) {
out <- lapply(ci, function(i) {
.ci <- stats::confint(x, level = i, ...)
rn <- rownames(.ci)
.data_frame(
Parameter = gsub("^(.*):(.*)", "\\2", rn),
CI = i,
CI_low = .ci[, 1],
CI_high = .ci[, 2],
Response = gsub("^(.*):(.*)", "\\1", rn)
)
})
out <- .remove_backticks_from_parameter_names(do.call(rbind, out))
} else {
out <- .data_frame(ci_wald(x, ci = ci, ...), Response = insight::get_parameters(x)$Response)
}
out
}
#' @importFrom insight find_response
#' @export
simulate_model.mlm <- function(model, iterations = 1000, ...) {
responses <- insight::find_response(model, combine = FALSE)
out <- .simulate_model(model, iterations, component = "conditional", effects = "fixed")
cn <- paste0(colnames(out), rep(responses, each = length(colnames(out)) / length(responses)))
colnames(out) <- cn
class(out) <- c("parameters_simulate_model", class(out))
attr(out, "object_name") <- .safe_deparse(substitute(model))
out
}
#' @export
simulate_parameters.mlm <- function(model,
iterations = 1000,
centrality = "median",
ci = .95,
ci_method = "quantile",
test = "p-value",
...) {
data <- simulate_model(model, iterations = iterations, ...)
out <-
.summary_bootstrap(
data = data,
test = test,
centrality = centrality,
ci = ci,
ci_method = ci_method,
...
)
out$Response <- NA
responses <- insight::find_response(model, combine = FALSE)
for (i in responses) {
out$Response[grepl(paste0(i, "$"), out$Parameter)] <- i
out$Parameter <- gsub(paste0(i, "$"), "", out$Parameter)
}
class(out) <- c("parameters_simulate", "see_parameters_simulate", class(out))
attr(out, "object_name") <- deparse(substitute(model), width.cutoff = 500)
attr(out, "object_class") <- class(model)
attr(out, "iterations") <- iterations
attr(out, "ci") <- ci
out
}
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