*! version 2.0 05may2021

Syntax

Fixed- and random-effects inverse-variance weighted
meta-analytic regression (aka: meta-regression).

mareg indepvars [if] [in] ,
var(varname)
w(varname)
se(varname)
[_options_]

where effectsize is the effect size variable and
indepvar is one or more independent variable (moderator). The
effect size can be any effect size type, such as Cohen's d,
Hedges' g, logged odds ratio, logged risk ratio, logged logit,
r or Fisher's Zr, among others. It is critical that the
effect size is in its analyzable form. For example, the effect size
can be a logged odds ratio but not an odds ratio. One of the following
must also be specified:

o var(varname): the variance of the effect size

o w(varname): the inverse variance weight of the effect size

o se(varname): the standard error of the effect size

The relationship among these is assumed to be w =
1/var = 1/se^2.

Options

Model Type
model(_string_)
model type; default is REML (restricted maximum likelihood); options
include FE (fixed effect), DL (Dersimonian & Laird), HE (Hedges'), HS
(Hunter & Schmidt), SJ (Sidik-Jonkman), SJIT (Sidik-Jonkman,
iterative), ML (maximum likelihood), REML (restricted maximum
likelihood), and EB (empirical bayes)

Description

mareg performs meta-analytic regression (aka:
meta-regression, moderator analysis) under either a fixed-effect model
(also called a common-effect model) or a random-effects model. Several
estimators for the random effects variance component (tau^2) are
available. The command requires an effect size, its associated
standard error, variance, or inverse variance weight, and a one or
more independent variables.

Subgroup or categorical moderator analysis (i.e.,
analog-to-the-ANOVA) can be performed with the maanova command
(see maanova). For a basic meta-analysis returning the overall
mean effect size and associated statistics, see masum command
(see masum).

As of Stata version 16.0, Stata has a built-in command for
conducting meta-analysis. See meta.

Acknowledgments

mareg was written by David B. Wilson and is an updated
version of a command written as a companion to a book on meta-analysis
he co-authored with Mark Lipsey (Lipsey & Wilson, 2001). Portions of
this program are based on code from Wolfgang Viechtbauer's
metafor package for R.

References

Lipsey, M. W., & Wilson, D. B. (2001). Practical
meta-analysis. Sage.