.ma_generic

Internal function for computing bare-bones meta-analyses of generic effect sizes

internal

Tools for computing bare-bones and psychometric meta-analyses and for generating psychometric data for use in meta-analysis simulations. Supports bare-bones, individual-correction, and artifact-distribution methods for meta-analyzing correlations and d values. Includes tools for converting effect sizes, computing sporadic artifact corrections, reshaping meta-analytic databases, computing multivariate corrections for range variation, and more. Bugs can be reported to <https://github.com/psychmeta/psychmeta/issues> or <issues@psychmeta.com>.

Jeffrey A. Dahlke

psychmeta

Psychometric Meta-Analysis Toolkit

Brenton M. Wiernik

Wesley Gardiner

Michael T. Brannick

Jack Kostal

Sean Potter

John Sakaluk

Yuejia (Mandy) Teng

.ma_generic function

<dl><dt>data</dt>
<dd>Data frame of bare-bones information.</dd>
<dt>run_lean</dt>
<dd>If TRUE, the meta-analysis will not generate an escalc object. Meant to speed up bootstrap analyses that do not require supplemental output.</dd>
<dt>ma_arg_list</dt>
<dd>List of arguments to be used in the meta-analysis function.</dd></dl>

Arguments

Internal function for computing bare-bones meta-analyses of generic effect sizes — .ma_generic

<dl>

<dt>data</dt>
<dd>Data frame of bare-bones information.</dd>


<dt>run_lean</dt>
<dd>If TRUE, the meta-analysis will not generate an escalc object. Meant to speed up bootstrap analyses that do not require supplemental output.</dd>


<dt>ma_arg_list</dt>
<dd>List of arguments to be used in the meta-analysis function.</dd>

</dl>

Internal function for computing bare-bones meta-analyses of generic effect sizes

.ma_generic: Internal function for computing bare-bones meta-analyses of generic effect sizes

Description

Usage

Value

Arguments