Table B1.

Features of software for meta‐analysis

		Meta‐Essentials	CMA	Commands for Stata Discussed by Palmer and Sterne11	meta and metafor package for R
Basic characteristics	Version	1.1	3.3.070	Versions available from the statistical software components archive on April 20, 2017. eg, metan 3.04, metareg 2.6.1, and metafunnel 1.0.2. Stata 14.1	meta 4.8–0 metafor 1.9–9. R 3.3.3
	Website	www.meta‐essentials.om	www.meta‐analysis.om	http://www.stata‐press.com/books/meta‐analysis‐in‐stata/	meta: http://meta‐analysis‐with‐r.org metafor: http://www.metafor‐project.org/
	Freeware/commercial	Freeware	Commercial	Freeware	Freeware
	Prerequisite software	Microsoft Excel (commercial)	None	Stata (commercial)	R (freeware)
	Operating systems	Windows, Mac OS	Windows	Windows, Mac OS, Linux	Windows, Mac OS, Linux
Supporting material	Documentation	User manual, website, this paper	Borenstein et al,1 website, and tutorials	Palmer and Sterne,11 website, and help function in Stata	meta: Schwarzer et al,74 website, and help function in R metafor: Viechtbauer,16 website, and help function in R
Input	Effect size calculation	d and r families	d and r families	d and r families	d and r families
Method settings	User interface	Graphical user interface	Graphical user interface	Syntax	Syntax
	Adaptability	Full	Limited	Full	Full
	Between‐study variance estimators	DL	DL, (RE)	DL, EB, HE, (RE), SJ	meta: DL, PM metafor: DL, EB, HE, HS, PM, (RE)ML, SJ
	Weighting methods	IV, MH, Peto	IV, MH, Peto	IV, MH, Peto	IV, MH, Peto
Output	Confidence and prediction interval	Both	CI only	Both available, CI default	Both available, CI default
	Confidence interval distributions	KNHA Student's t	Normal or Student's t (KNHA Student's t in meta‐regression)	Normal or KNHA Student's t	Normal or KNHA Student's t
	Automated forest plot	Yes	Yes	Yes	Yes
	Subgroup‐analyses	Yes	Yes	Yes	Yes
	Meta‐regression	Yes, single covariate	Yes, multiple covariates	Yes, multiple covariates	Yes, multiple covariates
	Funnel plot and trim‐and‐fill	Yes	Yes	Yes	Yes
	Failsafe‐N	Yes	Yes	Yes	meta: No metafor: Yes

		MIX Pro	OpenMeta[Analyst]	RevMan	Syntaxes for SPSS by Field land Gillett17 and Wilson18
Basic characteristics	Version	2.0.1.5	None indicated	5.3.5	Field and Gillett: Version number not provided. Website last updated September 2010. Wilson: Version number not provided. SPSS statistics syntax file in. Zip‐file dates from September 20, 2006. SPSS 23.0.0.0
	Website	http://www.meta‐analysis‐made‐easy.com/	http://www.cebm.brown.edu/openmeta/	http://tech.cochrane.org/revman	Field and Gillett: https://www.discoveringstatistics.com/repository/fieldgillett/how_to_do_a_meta_analysis.html Wilson: http://mason.gmu.edu/~dwilsonb/ma.html
	Freeware / commercial	Commercial	Freeware	Freeware	Freeware
	Prerequisite software	Microsoft excel (commercial)	None	None	SPSS (commercial)
	Operating systems	Windows	Windows (only 64‐bit) and Mac OS	Windows, Mac OS, Linux	Windows, Mac OS, Linux
Supporting material	Documentation	Tips & tricks and meta‐tutor (embedded)	Wallace et al.13 and website	Cochrane handbook19 and user guide	Field and Gillett: Field and Gillett17 and website Wilson: Lipsey and Wilson84 and website
Input	Effect size calculation	d family	d family	d family	No
Method settings	User interface	Graphical user interface	Graphical user interface and syntax	Graphical user interface	Syntax
	Adaptability	Limited	Full	Limited	Full
	Between‐study variance estimators	DL	DL, EB, HE, HS, PM, (RE), SJ	DL	Field and Gillett: DL, HS Wilson: DL, (RE)ML
	Weighting methods	IV, MH	IV, MH, Peto	IV, MH, Peto	IV
Output	Confidence and prediction interval	CI only	CI only	Both	CI only
	Confidence interval distributions	Normal or Student's t	Normal or KNHA Student's t	Normal	Normal
	Automated forest plot	Yes	Yes	Yes	No
	Subgroup‐analyses	Yes	Yes	Yes	No
	Meta‐regression	Yes, single covariate	Yes, multiple covariates	No	Yes, multiple covariates
	Funnel plot and trim‐and‐fill	Yes	No	Yes; No trim and fill	Field and Gillet: Only funnel plot Wilson: No
	Failsafe‐N	Yes	No	No	Field and Gillet: Yes Wilson: No

Abbreviations: Between‐study variance estimators include the following: DL, DerSimonian‐Laird; (RE)ML, (Restricted) Maximum Likelihood; PM, Paule‐Mandel; HE, Hedges; SJ, Sidik‐Jonkman; and EB, Empirical Bayes. Models for calculating the weights of individual studies include the following: IV, inverse variance; MH, Mantel‐Haenszel; and Peto. CIs can be based on the standard normal distribution, the Student's t distribution, or the Student's t distribution with KNHA; see Section 3.2.5.