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# confidence intervals --------------------------
#' @export
ci.mipo <- ci.gam
#' @export
ci.mira <- function(x, ci = 0.95, ...) {
insight::check_if_installed("mice")
ci(mice::pool(x), ci = ci, ...)
}
# p values ---------------------------------------
#' @export
p_value.mipo <- function(model, ...) {
s <- summary(model)
out <- .data_frame(
Parameter = as.vector(s$term),
p = as.vector(s$p.value)
)
# check for ordinal-alike models
if (!is.null(model$pooled) && "y.level" %in% colnames(model$pooled)) {
out$Response <- as.vector(model$pooled$y.level)
}
out
}
#' @export
p_value.mira <- function(model, ...) {
insight::check_if_installed("mice")
p_value(mice::pool(model), ...)
}
# standard errors --------------------------------
#' @export
standard_error.mipo <- function(model, ...) {
s <- summary(model)
out <- .data_frame(
Parameter = as.vector(s$term),
SE = as.vector(s$std.error)
)
# check for ordinal-alike models
if (!is.null(model$pooled) && "y.level" %in% colnames(model$pooled)) {
out$Response <- as.vector(model$pooled$y.level)
}
out
}
#' @export
standard_error.mira <- function(model, ...) {
insight::check_if_installed("mice")
standard_error(mice::pool(model), ...)
}
# format -------------------------------------------
#' @export
format_parameters.mira <- format_parameters.rma
# model_parameters ---------------------------------
#' @export
model_parameters.mipo <- function(model,
ci = 0.95,
exponentiate = FALSE,
p_adjust = NULL,
keep = NULL,
drop = NULL,
verbose = TRUE,
...) {
# validation check, warn if unsupported argument is used.
dot_args <- .check_dots(
dots = list(...),
not_allowed = c("vcov", "vcov_args"),
class(model)[1],
verbose = verbose
)
# check if we have ordinal/categorical response
if (!is.null(model$pooled) && "y.level" %in% colnames(model$pooled)) {
merge_by <- c("Parameter", "Response")
} else {
merge_by <- "Parameter"
}
fun_args <- list(
model,
ci = ci,
merge_by = merge_by,
exponentiate = exponentiate,
p_adjust = p_adjust,
keep_parameters = keep,
drop_parameters = drop,
vcov = NULL,
vcov_args = NULL
)
fun_args <- c(fun_args, dot_args)
out <- do.call(".model_parameters_generic", fun_args)
attr(out, "object_name") <- insight::safe_deparse_symbol(substitute(model))
out
}
#' Parameters from multiply imputed repeated analyses
#'
#' Format models of class `mira`, obtained from `mice::width.mids()`, or of
#' class `mipo`.
#'
#' @param model An object of class `mira` or `mipo`.
#' @inheritParams model_parameters.default
#' @param ... Arguments passed to or from other methods.
#'
#' @details `model_parameters()` for objects of class `mira` works
#' similar to `summary(mice::pool())`, i.e. it generates the pooled summary
#' of multiple imputed repeated regression analyses.
#'
#' @examplesIf require("mice", quietly = TRUE) && require("gee", quietly = TRUE)
#' library(parameters)
#' data(nhanes2, package = "mice")
#' imp <- mice::mice(nhanes2)
#' fit <- with(data = imp, exp = lm(bmi ~ age + hyp + chl))
#' model_parameters(fit)
#' \donttest{
#' # model_parameters() also works for models that have no "tidy"-method in mice
#' data(warpbreaks)
#' set.seed(1234)
#' warpbreaks$tension[sample(1:nrow(warpbreaks), size = 10)] <- NA
#' imp <- mice::mice(warpbreaks)
#' fit <- with(data = imp, expr = gee::gee(breaks ~ tension, id = wool))
#'
#' # does not work:
#' # summary(mice::pool(fit))
#'
#' model_parameters(fit)
#' }
#'
#' # and it works with pooled results
#' data("nhanes2", package = "mice")
#' imp <- mice::mice(nhanes2)
#' fit <- with(data = imp, exp = lm(bmi ~ age + hyp + chl))
#' pooled <- mice::pool(fit)
#'
#' model_parameters(pooled)
#' @export
model_parameters.mira <- function(model,
ci = 0.95,
exponentiate = FALSE,
p_adjust = NULL,
keep = NULL,
drop = NULL,
verbose = TRUE,
...) {
insight::check_if_installed("mice")
micemodel <- suppressWarnings(mice::pool(model))
out <- .model_parameters_generic(
model = micemodel,
ci = ci,
bootstrap = FALSE,
iterations = 10,
merge_by = "Parameter",
standardize = NULL,
exponentiate = exponentiate,
p_adjust = p_adjust,
keep_parameters = keep,
drop_parameters = drop,
verbose = verbose,
...
)
attr(out, "object_name") <- insight::safe_deparse_symbol(substitute(model))
out
}
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