build.basesub

Make a data set of all possible pairwise substitution of a composition which can be used as
the base for substitution models.

Implement Bayesian Multilevel Modelling for compositional data
in a multilevel framework. Compute multilevel compositional data and
Isometric log ratio (ILR) at between and within-person levels,
fit Bayesian multilevel models for compositional predictors and outcomes,
and run post-hoc analyses such as isotemporal substitution models.
References:
Le, Stanford, Dumuid, and Wiley (2024) <doi:10.48550/arXiv.2405.03985>,
Le, Dumuid, Stanford, and Wiley (2024) <doi:10.48550/arXiv.2411.12407>.

Flora Le

multilevelcoda

Estimate Bayesian Multilevel Models for Compositional Data

Joshua F. Wiley

build.basesub function

<dl><dt>parts</dt>
<dd>A character vector specifying the names of compositional variables to be used.</dd>
<dt>comparison</dt>
<dd>Either <code>"one-to-one"</code> or <code>"one-to-all"</code>. Default is <code>"one-to-one"</code>.</dd></dl>

Arguments

Build Base Pairwise Substitution — build.basesub

<dl>

<dt>parts</dt>
<dd>A character vector specifying the names of compositional variables to be used.</dd>


<dt>comparison</dt>
<dd>Either <code>"one-to-one"</code> or <code>"one-to-all"</code>. Default is <code>"one-to-one"</code>.</dd>

</dl>

build.basesub: Build Base Pairwise Substitution

Description

Usage

Value

Arguments

Examples