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# Package nlme; .lme, .gls
############### .lme --------------
#' @export
model_parameters.lme <- model_parameters.merMod
#' @export
ci.lme <- function(x,
ci = 0.95,
vcov = NULL,
vcov_args = NULL,
method = "wald",
...) {
method <- tolower(method)
method <- match.arg(method, choices = c("wald", "normal", "residual", "betwithin", "ml1"))
if (method %in% c("wald", "residual", "normal")) {
# `vcov` argument must be computed using the `.ci_generic` function.
# note that this uses `dof()`, which produces slightly different results than the stock degrees of freedom
if (!is.null(vcov) || !requireNamespace("nlme", quietly = TRUE)) {
.ci_generic(model = x, ci = ci, method = method, vcov = vcov, vcov_args = vcov_args, ...)
} else {
insight::check_if_installed("nlme")
out <- lapply(ci, function(i) {
ci_list <- tryCatch(
{
nlme::intervals(x, level = i, ...)
},
error = function(e) {
nlme::intervals(x, level = i, which = "fixed", ...)
}
)
.data_frame(
Parameter = rownames(ci_list$fixed),
CI = i,
CI_low = as.vector(ci_list$fixed[, "lower"]),
CI_high = as.vector(ci_list$fixed[, "upper"])
)
})
insight::text_remove_backticks(do.call(rbind, out), verbose = FALSE)
}
# ml1 approx
} else if (method == "ml1") {
ci_ml1(x, ci)
# betwithin approx
} else if (method == "betwithin") {
ci_betwithin(x, ci)
}
}
#' @export
p_value.lme <- function(model,
vcov = NULL,
vcov_args = NULL,
...) {
# default values
if (is.null(vcov)) {
cs <- stats::coef(summary(model))
p <- cs[, 5]
param <- rownames(cs)
# robust standard errors or custom varcov
} else {
b <- insight::get_parameters(model)
se <- standard_error(model, vcov = vcov, vcov_args = vcov_args, ...)
tstat <- b$Estimate / se$SE
# residuals are defined like this in `nlme:::summary.lme`
dof <- model$fixDF[["X"]]
p <- 2 * stats::pt(-abs(tstat), df = dof)
param <- se$Parameter
}
.data_frame(
Parameter = .remove_backticks_from_string(param),
p = as.vector(p)
)
}
#' @export
standard_error.lme <- standard_error.default
############### .gls --------------
#' @export
standard_error.gls <- standard_error.default
#' @export
p_value.gls <- p_value.default
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