complete_levels

<p><code>model.matrix</code> breaks when <code>newdata</code> includes a factor
variable, but not all levels are present in the data. This is bad for us
because we often want to get predictions with one (or few) rows, where some
factor levels are inevitably missing.</p>

internal

Compute and plot predictions, slopes, marginal means, and comparisons (contrasts, risk ratios, odds, etc.) for over 100 classes of statistical and machine learning models in R. Conduct linear and non-linear hypothesis tests, or equivalence tests. Calculate uncertainty estimates using the delta method, bootstrapping, or simulation-based inference. Details can be found in Arel-Bundock, Greifer, and Heiss (2024) <doi:10.18637/jss.v111.i09>.

Vincent Arel-Bundock

marginaleffects

Predictions, Comparisons, Slopes, Marginal Means, and Hypothesis
Tests

Noah Greifer

Etienne Bacher

Grant McDermott

Andrew Heiss

complete_levels function

Create a data.frame with all factor or character levels — complete_levels

Create a data.frame with all factor or character levels

complete_levels: Create a data.frame with all factor or character levels

Description

Usage

Arguments