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# plm package: .plm, .pgmm, .pggls
# plm ---------------------------
#' @export
standard_error.plm <- function(model, vcov = NULL, vcov_args = NULL, verbose = TRUE, ...) {
dots <- list(...)
se <- NULL
se_standard <- stats::coef(summary(model))
# vcov: matrix
if (is.matrix(vcov)) {
se <- sqrt(diag(vcov))
}
# vcov: function which returns a matrix
if (is.function(vcov)) {
fun_args <- c(list(model), vcov_args, dots)
se <- .safe(sqrt(diag(do.call("vcov", fun_args))))
}
# vcov: character (with backward compatibility for `robust = TRUE`)
if (is.character(vcov) || isTRUE(dots[["robust"]])) {
.vcov <- insight::get_varcov(
model,
vcov = vcov,
vcov_args = vcov_args,
verbose = verbose,
...
)
se <- sqrt(diag(.vcov))
}
if (is.null(se)) {
se <- as.vector(se_standard[, 2])
}
.data_frame(
Parameter = .remove_backticks_from_string(rownames(se_standard)),
SE = se
)
}
#' @export
p_value.plm <- p_value.default
# pggls ------------------------
#' @export
p_value.pggls <- function(model, ...) {
cs <- summary(model)$CoefTable
p <- cs[, 4]
.data_frame(
Parameter = .remove_backticks_from_string(rownames(cs)),
p = as.vector(p)
)
}
# pgmm --------------------
#' @export
model_parameters.pgmm <- function(model,
ci = 0.95,
component = c("conditional", "all"),
exponentiate = FALSE,
p_adjust = NULL,
keep = NULL,
drop = NULL,
verbose = TRUE,
...) {
component <- match.arg(component)
params <- .extract_parameters_generic(
model,
merge_by = c("Parameter", "Component"),
ci = ci,
component = component,
p_adjust = p_adjust,
keep_parameters = keep,
drop_parameters = drop,
...
)
# exponentiate coefficients and SE/CI, if requested
params <- .exponentiate_parameters(params, model, exponentiate)
params <- .add_model_parameters_attributes(
params,
model,
ci,
exponentiate,
p_adjust = p_adjust,
verbose = verbose,
...
)
attr(params, "object_name") <- insight::safe_deparse_symbol(substitute(model))
class(params) <- c("parameters_model", "see_parameters_model", class(params))
params
}
#' @export
standard_error.pgmm <- function(model, component = c("conditional", "all"), ...) {
component <- match.arg(component)
params <- insight::get_parameters(model, component = component, ...)
se <- sqrt(diag(insight::get_varcov(model, component = component, ...)))
.data_frame(
Parameter = params$Parameter,
SE = as.vector(se)
)
}
#' @export
ci.pgmm <- function(x, ci = 0.95, dof = Inf, method = NULL, component = "conditional", ...) {
if (is.null(method)) {
method <- "wald"
} else {
method <- tolower(method)
}
.ci_generic(model = x, ci = ci, dof = dof, method = method, component = component)
}
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