Closed jmgirard closed 2 months ago
standardize_parameters()
~is now @strengejacke's problem~ now lives in {parameters}
(:
You could - for now - workaround this by using:
fit <- lm(Sepal.Length ~ Species, data = iris)
parameters::model_parameters(fit, standardize = "refit")
#> Parameter | Coefficient | SE | 95% CI | t(147) | p
#> ----------------------------------------------------------------------------
#> (Intercept) | -1.01 | 0.09 | [-1.18, -0.84] | -11.50 | < .001
#> Species [versicolor] | 1.12 | 0.12 | [ 0.88, 1.37] | 9.03 | < .001
#> Species [virginica] | 1.91 | 0.12 | [ 1.66, 2.16] | 15.37 | < .001
#>
#> Uncertainty intervals (equal-tailed) and p-values (two-tailed) computed
#> using a Wald t-distribution approximation.
Created on 2024-06-23 with reprex v2.1.0
Note the difference between
model_parameters()
andstandardize_parameters()
:Created on 2024-06-10 with reprex v2.1.0