lmcpp

Used to get marginal coefficients off of a generalized linear mixed model.

Calculate Bayesian marginal effects, average marginal effects, and marginal coefficients (also called population averaged coefficients) for models fit using the 'brms' package including fixed effects, mixed effects, and location scale models. These are based on marginal predictions that integrate out random effects if necessary (see for example <doi:10.1186/s12874-015-0046-6> and <doi:10.1111/biom.12707>).

Joshua F Wiley

brmsmargins

Bayesian Marginal Effects for 'brms' Models

Joshua F. Wiley

Donald Hedeker

lmcpp function

<dl><dt>X</dt>
<dd>A numeric model matrix. If intercept is desired, it must already have been added as a column.</dd>
<dt>y</dt>
<dd>A numeric matrix. A single column if one response variable or multiple columns
where each column is a different response, such as a for marginal coefficients where
each column is a different MCMC sample.</dd></dl>

Arguments

Fast Linear Regression — lmcpp

<dl>

<dt>X</dt>
<dd>A numeric model matrix. If intercept is desired, it must already have been added as a column.</dd>


<dt>y</dt>
<dd>A numeric matrix. A single column if one response variable or multiple columns
where each column is a different response, such as a for marginal coefficients where
each column is a different MCMC sample.</dd>

</dl>

lmcpp: Fast Linear Regression

Description

Usage

Value

Arguments

Examples