Q_selected_size_GS

A function returns the Q-between from the tree with given size

internal

Meta-CART integrates classification and regression trees (CART) into meta-analysis. Meta-CART is a flexible approach to identify interaction effects between moderators in meta-analysis. The method is described in Dusseldorp et al. (2014) <doi:10.1037/hea0000018> and Li et al. (2017) <doi:10.1111/bmsp.12088>.

Juan Claramunt Gonzalez

metacart

Meta-CART: A Flexible Approach to Identify Moderators in
Meta-Analysis

Xinru Li

Elise Dusseldorp

Kaihua Liu

Juan Claramunt

Jacqueline Meulman

Q_selected_size_GS function

<dl><dt>tree</dt>
<dd>A initial tree fitted by rpart, needs to an rpart object.</dd>
<dt>nsplit</dt>
<dd>the required number of splits</dd>
<dt>mods</dt>
<dd>the moderators found by the tree.</dd>
<dt>minbucket</dt>
<dd>the minimum number of observations in any terminal &lt;leaf&gt; node.</dd>
<dt>minsplit</dt>
<dd>the minimum number of observations that must exist in a node in order for a split to be attempted.</dd>
<dt>...</dt>
<dd>Additional arguments passed to prune.rpart().</dd></dl>

Arguments

A function returns the Q-between from the tree with given size — Q_selected_size_GS

<dl>

<dt>tree</dt>
<dd>A initial tree fitted by rpart, needs to an rpart object.</dd>


<dt>nsplit</dt>
<dd>the required number of splits</dd>


<dt>mods</dt>
<dd>the moderators found by the tree.</dd>


<dt>minbucket</dt>
<dd>the minimum number of observations in any terminal &lt;leaf&gt; node.</dd>


<dt>minsplit</dt>
<dd>the minimum number of observations that must exist in a node in order for a split to be attempted.</dd>


<dt>...</dt>
<dd>Additional arguments passed to prune.rpart().</dd>

</dl>

Q_selected_size_GS: A function returns the Q-between from the tree with given size

Description

Usage

Value

Arguments