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# Packages lavaan, blavaan
# model parameters ---------------------------
#' @rdname model_parameters.principal
#' @export
model_parameters.lavaan <- function(model,
ci = 0.95,
standardize = FALSE,
component = c("regression", "correlation", "loading", "defined"),
keep = NULL,
drop = NULL,
verbose = TRUE,
...) {
params <- .extract_parameters_lavaan(model,
ci = ci,
standardize = standardize,
keep_parameters = keep,
drop_parameters = drop,
verbose = verbose,
...
)
# Filter
if (all(component == "all")) {
component <- c("regression", "correlation", "loading", "variance", "defined", "mean")
}
params <- params[tolower(params$Component) %in% component, ]
# add class-attribute for printing
class(params) <- c("parameters_sem", "see_parameters_sem", class(params))
attr(params, "ci") <- ci
attr(params, "model") <- model
params
}
#' @export
model_parameters.blavaan <- function(model,
centrality = "median",
dispersion = FALSE,
ci = 0.95,
ci_method = "eti",
test = "pd",
rope_range = "default",
rope_ci = 0.95,
diagnostic = c("ESS", "Rhat"),
component = "all",
standardize = NULL,
keep = NULL,
drop = NULL,
verbose = TRUE,
...) {
# Processing
params <- .extract_parameters_bayesian(
model,
centrality = centrality,
dispersion = dispersion,
ci = ci,
ci_method = ci_method,
test = test,
rope_range = rope_range,
rope_ci = rope_ci,
diagnostic = diagnostic,
effects = "all",
standardize = standardize,
keep_parameters = keep,
drop_parameters = drop,
verbose = verbose,
...
)
# Filter
if (!all(component == "all")) {
params <- params[tolower(params$Component) %in% component, ]
}
params <- .add_model_parameters_attributes(
params,
model,
ci,
exponentiate = FALSE,
ci_method = ci_method,
verbose = verbose,
...
)
attr(params, "object_name") <- insight::safe_deparse_symbol(substitute(model))
class(params) <- c("parameters_sem", "see_parameters_sem", class(params))
params
}
# ci ---------------------------
#' @export
ci.lavaan <- function(x, ci = 0.95, ...) {
out <- .extract_parameters_lavaan(model = x, ci = ci, ...)
out$CI <- ci
out[out$Operator != "~1", c("To", "Operator", "From", "CI", "CI_low", "CI_high")]
}
# SE ---------------------------
#' @export
standard_error.lavaan <- function(model, ...) {
out <- .extract_parameters_lavaan(model, ...)
out[out$Operator != "~1", c("To", "Operator", "From", "SE")]
}
#' @export
standard_error.blavaan <- function(model, ...) {
params <- insight::get_parameters(model, ...)
.data_frame(
Parameter = colnames(params),
SE = unname(sapply(params, stats::sd, na.rm = TRUE))
)
}
# p-value ---------------------------
#' @export
p_value.lavaan <- function(model, ...) {
out <- .extract_parameters_lavaan(model, ...)
out[out$Operator != "~1", c("To", "Operator", "From", "p")]
}
#' @export
p_value.blavaan <- p_value.BFBayesFactor
# print ---------------------------
#' @export
print.parameters_sem <- function(x, digits = 2, ci_digits = digits, p_digits = 3, ...) {
# check if user supplied digits attributes
if (missing(digits)) {
digits <- .additional_arguments(x, "digits", 2)
}
if (missing(ci_digits)) {
ci_digits <- .additional_arguments(x, "ci_digits", digits)
}
if (missing(p_digits)) {
p_digits <- .additional_arguments(x, "p_digits", 3)
}
verbose <- .additional_arguments(x, "verbose", TRUE)
formatted_table <- format(
x = x,
digits = digits,
ci_digits,
p_digits = p_digits,
format = "text",
ci_brackets = TRUE,
ci_width = "auto",
...
)
cat(insight::export_table(formatted_table, format = "text", ...))
if (isTRUE(verbose)) {
.print_footer_cimethod(x)
}
invisible(x)
}
#' @export
#' @inheritParams stats::predict
predict.parameters_sem <- function(object, newdata = NULL, ...) {
insight::check_if_installed("lavaan")
as.data.frame(lavaan::lavPredict(
attributes(object)$model,
newdata = newdata,
method = "EBM",
...
))
}
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