Table Of ContentMeta-Analysis in Stata:
An Updated Collection from the Stata Journal
2
Second Edition
TOM M. PALMER, collection editor Department of Mathematics and
Statistics Lancaster University Lancaster, UK
JONATHAN A. C. STERNE, collection editor School of Social and
Community Medicine University of Bristol Bristol, UK
H. JOSEPH NEWTON, Stata Journal editor Department of Statistics
Texas A&M University College Station, TX
NICHOLAS J. COX, Stata Journal editor Department of Geography
Durham University Durham City, UK
®
A Stata Press Publication StataCorp LP College Station, Texas
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Copyright © 2009, 2016 by StataCorp LP
All rights reserved. First edition 2009
Second edition 2016
Published by Stata Press, 4905 Lakeway Drive, College Station, Texas 77845
Typeset in LATEX 2
Printed in the United States of America
10 9 8 7 6 5 4 3 2 1
Print ISBN-10: 1-59718-147-1
Print ISBN-13: 978-1-59718-147-1
ePub ISBN-10: 1-59718-221-4
ePub ISBN-13: 978-1-59718-221-8
Mobi ISBN-10: 1-59718-222-2
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Mobi ISBN-13: 978-1-59718-222-5
Library of Congress Control Number: 2015950607
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Stata and Stata Press are registered trademarks with the World Intellectual Property
Organization of the United Nations.
LATEX 2 is a trademark of the American Mathematical Society.
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Contents
Introduction to the second edition
References
Introduction to the first edition
References
Install the software
I Meta-analysis in Stata: metan, metaan, metacum, and metap
References
1 metan—a command for meta-analysis in Stata
1.1 Background
1.2 Data structure
1.3 Analysis of binary data using fixed-effects models
1.4 Analysis of continuous data using fixed-effects models
1.5 Test for heterogeneity
1.6 Analysis of binary or continuous data using random-effects models
1.7 Tests of overall effect
1.8 Graphical analyses
1.9 Syntax for metan
1.10 Options for metan
1.11 Saved results from metan (macros)
1.12 Syntax for funnel
1.13 Options for funnel
1.14 Syntax for labbe
1.15 Options for labbe
1.16 Example 1: Interventions in smoking cessation
1.17 Example 2
1.18 Formulas
1.19 Individual study responses: binary outcomes
1.20 Individual study responses: continuous outcomes
1.21 Mantel–Haenszel methods for combining trials
1.22 Inverse variance methods for combining trials
1.23 Peto’s assumption free method for combining trials
1.24 DerSimonian and Laird random-effects models
1.25 Confidence intervals
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1.26 Test statistics
1.27 Acknowledgments
1.28 References
2 metan: fixed- and random-effects meta-analysis
2.1 Introduction
2.2 Example data
2.3 Syntax
2.4 Basic use
2.5 Displaying data columns in graphs
2.6 by() processing
2.7 User-defined analyses
2.8 New analysis options
2.9 New output
2.10 More graph options
2.11 Variables and results produced by metan
2.12 References
3 metaan: Random-effects meta-analysis
3.1 Introduction
3.2 The metaan command
3.3 Methods
3.4 Example
3.5 Discussion
3.6 Acknowledgments
3.7 References
4 Cumulative meta-analysis
4.1 Syntax
4.2 Options
4.3 Background
4.4 Example
4.5 Note
4.6 Acknowledgments
4.7 References
5 Meta-analysis of p-values
5.1 Fisher’s method
5.2 Edgington’s methods
5.3 Syntax
5.4 Option
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5.5 Example
5.6 Individual or frequency records
5.7 Saved results
5.8 References
II Meta-regression: metareg
References
6 Meta-regression in Stata
6.1 Introduction
6.2 Basis of meta-regression
6.3 Relation to other Stata commands
6.4 Background to examples
6.5 New and enhanced features
6.6 Syntax, options, and saved results
6.7 Methods and formulas
6.8 Acknowledgments
6.9 References
7 Meta-analysis regression
7.1 Background
7.2 Method-of-moments estimator
7.3 Iterative procedures
7.4 Syntax
7.5 Options
7.6 Example
7.7 Saved results
7.8 Acknowledgments
7.9 References
III Investigating bias in meta-analysis: metafunnel, confunnel, metabias,
metatrim, and extfunnel
References
8 Funnel plots in meta-analysis
8.1 Introduction
8.2 Funnel plots
8.3 Syntax
8.4 Description
8.5 Options
8.6 Examples
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8.7 Acknowledgments
8.8 References
9 Contour-enhanced funnel plots for meta-analysis
9.1 Introduction
9.2 Contour-enhanced funnel plots
9.3 The confunnel command
9.4 Use of confunnel
9.5 Discussion
9.6 References
10 Updated tests for small-study effects in meta-analyses
10.1 Introduction
10.2 Syntax
10.3 Options
10.4 Background
10.5 Example
10.6 Saved results
10.7 Discussion
10.8 Acknowledgment
10.9 References
11 Tests for publication bias in meta-analysis
11.1 Syntax
11.2 Description
11.3 Options
11.4 Input variables
11.5 Explanation
11.6 Begg’s test
11.7 Egger’s test
11.8 Examples
11.9 Saved results
11.10 References
12 Tests for publication bias in meta-analysis
12.1 Modification of the metabias program
12.2 References
13 Nonparametric trim and fill analysis of publication bias in meta-
analysis
13.1 Syntax
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13.2 Description
13.3 Options
13.4 Specifying input variables
13.5 Explanation
13.6 Estimators of the number of suppressed studies
13.7 The iterative trim and fill algorithm
13.8 Example
13.9 Remarks
13.10 Saved results
13.11 Note
13.12 References
14 Graphical augmentations to the funnel plot to assess the impact of a
new study on an existing meta-analysis
14.1 Introduction
14.2 Methodology
14.3 The extfunnel command
14.4 Example uses of extfunnel
14.5 Additional feature
14.6 Discussion
14.7 Acknowledgments
14.8 References
IV Multivariate meta-analysis: metandi, mvmeta
References
15 metandi: Meta-analysis of diagnostic accuracy using hierarchical
logistic regression
15.1 Introduction
15.2 Example: Lymphangiography for diagnosis of lymph node
metastasis
15.3 Models for meta-analysis of diagnostic accuracy
15.4 metandi output
15.5 metandiplot
15.6 predict after metandi
15.7 Syntax and options for commands
15.8 Methods and formulas
15.9 Acknowledgments
15.10 References
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16 Multivariate random-effects meta-analysis
16.1 Introduction
16.2 Multivariate random-effects meta-analysis with mvmeta
16.3 Details of mvmeta
16.4 A utility command to produce data in the correct format:
mvmeta_make
16.5 Example 1: Telomerase data
16.6 Example 2: Fibrinogen Studies Collaboration data
16.7 Perfect prediction
16.8 Discussion
16.9 Acknowledgments
16.10 References
17 Multivariate random-effects meta-regression: Updates to mvmeta
17.1 Introduction
17.2 mvmeta: Multivariate random-effects meta-regression
17.3 Details
17.4 Example
17.5 Difficulties and limitations
17.6 Acknowledgments
17.7 References
V Individual patient data meta-analysis: ipdforest and ipdmetan
References
18 A short guide and a forest plot command (ipdforest) for one-stage
meta-analysis
18.1 Introduction
18.2 Individual patient data meta-analysis
18.3 The ipdforest command
18.4 Discussion
18.5 Acknowledgments
18.6 References
19 Two-stage individual participant data meta-analysis and generalized
forest plots
19.1 Introduction
19.2 Two-stage IPD meta-analysis
19.3 The ipdmetan command
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