find_second_split

A function to find the optimal combination of first two splits, 
and the corresponding Q-between given the first split

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

find_second_split function

<dl><dt>xk</dt>
<dd>moderator vector</dd>
<dt>first.splits</dt>
<dd>possible first splits</dd>
<dt>y</dt>
<dd>effect size</dd>
<dt>vi</dt>
<dd>sampling variance</dd>
<dt>minbucket</dt>
<dd>the minimal number of studies in child nodes</dd>
<dt>minsplit</dt>
<dd>the minimal number of studies in parent node</dd></dl>

Arguments

A function to find the optimal combination of first two splits, 
and the corresponding Q-between given the first split — find_second_split

<dl>

<dt>xk</dt>
<dd>moderator vector</dd>


<dt>first.splits</dt>
<dd>possible first splits</dd>


<dt>y</dt>
<dd>effect size</dd>


<dt>vi</dt>
<dd>sampling variance</dd>


<dt>minbucket</dt>
<dd>the minimal number of studies in child nodes</dd>


<dt>minsplit</dt>
<dd>the minimal number of studies in parent node</dd>

</dl>

find_second_split: A function to find the optimal combination of first two splits, and the corresponding Q-between given the first split

Description

Usage

Value

Arguments