.droplevels_as_needed

Missing levels can cause unexpected behavior when fitting a model after
setting contrasts. This function removes missing levels and informs the user
of how many levels were dropped from each factor.

internal

Quickly set and summarize contrasts for factors prior to regression analyses. Intended comparisons, baseline conditions, and intercepts can be explicitly set and documented without the user needing to directly manipulate matrices. Reviews and introductions for contrast coding are available in Brehm and Alday (2022)<doi:10.1016/j.jml.2022.104334> and Schad et al. (2020)<doi:10.1016/j.jml.2019.104038>.

Thomas Sostarics

contrastable

Consistent Contrast Coding for Factors

.droplevels_as_needed function

<dl><dt>model_data</dt>
<dd>Model data</dd>
<dt>lhs_variables</dt>
<dd>variables specified for contrast coding from formulas</dd>
<dt>verbose</dt>
<dd>Should messages be sent? Defaults to TRUE</dd></dl>

Arguments

Drop missing levels — .droplevels_as_needed

<dl>

<dt>model_data</dt>
<dd>Model data</dd>


<dt>lhs_variables</dt>
<dd>variables specified for contrast coding from formulas</dd>


<dt>verbose</dt>
<dd>Should messages be sent? Defaults to TRUE</dd>

</dl>

.droplevels_as_needed: Drop missing levels

Description

Usage

Value

Arguments