.ReplaceNA

Replace missing values by the overall weighted mean

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

.ReplaceNA function

<dl><dt>x1</dt>
<dd>the two-column matrix of the indices of missing values</dd>
<dt>x2</dt>
<dd>the matrix of predicted y with missing values</dd>
<dt>y</dt>
<dd>the effect size</dd>
<dt>vi</dt>
<dd>the sampling variance</dd>
<dt>tau2</dt>
<dd>the residual heterogeneity</dd></dl>

Arguments

Replace missing values by the overall weighted mean — .ReplaceNA

<dl>

<dt>x1</dt>
<dd>the two-column matrix of the indices of missing values</dd>


<dt>x2</dt>
<dd>the matrix of predicted y with missing values</dd>


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


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


<dt>tau2</dt>
<dd>the residual heterogeneity</dd>

</dl>

.ReplaceNA: Replace missing values by the overall weighted mean

Description

Usage

Arguments