Z-scores for M-Estimator parameters — z_scores • deli

Computes Wald-type Z-scores: \((\hat{\theta} - \theta_0) / \widehat{SE}(\hat{\theta})\).

This function mirrors m.z_scores() in Python delicatessen, so code translated from Python can keep its shape.

Usage

z_scores(object, null = 0, ...)

Arguments

object: A fitted MEstimator object (after calling estimate()).
null: Numeric null hypothesis value(s). Default 0.
...: Not used. Must be empty, so a name that is not one of the documented arguments is an error rather than silently ignored.

Value

A numeric vector of Z-scores.

See also

summary() and tidy(), which report the same Z-scores in table form alongside the other parameter-level results.

Examples

fit <- m_estimate(mpg ~ wt + hp, data = mtcars, .ee = ee_regression,
                  model = "linear")

z_scores(fit)
#> (Intercept)          wt          hp 
#>   19.199998   -6.255299   -4.780721