R/methods.R

In marginaleffects: Predictions, Comparisons, Slopes, Marginal Means, and Hypothesis Tests

#' @noRd

#' @noRd
#' @export
vcov.comparisons <- function(object, ...) {
    # align J and V: This might be a problematic hack, but I have not found examples yet.
    V <- attr(object, "vcov")
    J <- attr(object, "jacobian")
    aligned <- align_jacobian_vcov(J, V, object, ...)
    aligned$J %*% aligned$V %*% t(aligned$J)
}


#' @noRd
#' @export
vcov.predictions <- vcov.comparisons


#' @noRd
#' @export
vcov.hypotheses <- vcov.comparisons


#' @noRd
#' @export
vcov.slopes <- vcov.comparisons


#' @export
#' @noRd
coef.comparisons <- function(object, ...) {
    if (!is.null(object$estimate)) {
        out <- object$estimate
        if (is.null(names(out))) {
            lab <- tryCatch(get_labels(object), error = function(e) NULL)
            if (length(lab) == length(out)) {
                out <- stats::setNames(out, lab)
            }
        }
        return(out)
    } else {
        stop("The input object does not contain an 'estimate' element.")
    }
}


#' @export
#' @noRd
coef.slopes <- coef.comparisons


#' @export
#' @noRd
coef.predictions <- coef.comparisons


#' @export
#' @noRd
coef.hypotheses <- coef.comparisons


#' @export
#' @noRd
df.residual.comparisons <- function(object, ...) {
    out <- tryCatch(
        stats::df.residual(attr(object, "model")),
        error = function(e) NULL
    )
    if (is.null(out)) out <- Inf
    return(out)
}


#' @export
#' @noRd
df.residual.predictions <- df.residual.comparisons


#' @export
#' @noRd
df.residual.slopes <- df.residual.comparisons