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Meta-Analysis in Stata: An Updated Collection from the Stata Journal, Second Edition PDF

661 Pages·2015·19.576 MB·English
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Meta-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 ® 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 3 Mobi ISBN-13: 978-1-59718-222-5 Library of Congress Control Number: 2015950607 No part of this book may be reproduced, stored in a retrieval system, or transcribed, in any form or by any means—electronic, mechanical, photocopy, recording, or otherwise—without the prior written permission of StataCorp LP. Stata, , Stata Press, Mata, , and NetCourse are registered trademarks of StataCorp LP. 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. 4 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 5 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 6 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 7 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 8 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 9 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 10

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