Precomputed effect sizes effect size correlation, hr, or, mean difference, etc. We discuss the logit and double arcsine transformations to stabilise the variance. Metaanalysis is a method to obtain a weighted average of results from various studies. I think there are better tools for metaanalysis than stata. Heterogeneity in metaanalysis heterogeneity in metaanalysis refers to the variation in study outcomes between studies. An updated collection from the stata journal, second edition by tom m. Metaanalysis is a statistical technique for combining the results. Almost half of the studies were at high risk of bias. Creates a weblike analysis called a network diagram or network comparison. The metaanalysis of means procedure in ncss performs a metaanalysis on a set of twogroup, continuousscale studies. You declare this information once by using either meta set or meta esize, and it is then used by all meta commands. Compare comprehensive metaanalysis to revman, stata, spss, sas, excel. For continuous variables we need to combine measures, where the mean, standard deviation and.
The standardized mean difference smd with its corresponding 95% confidence interval ci was calculated. In stata, you perform metaregression by using meta regress. Metaanalysis has been characterized in various ways, from making order of scientific chaos to megasilliness, and has been subject of many debates however, time has taught both opponents and proponents that things are not black and white. To examine empirically whether the mean difference md or the standardised mean difference smd is more generalizable and statistically powerful in metaanalyses of continuous outcomes when the same unit is used. With these three data, the meta analysis could compute a summary effect size the summary difference in mean, and the standard deviation of the summary difference in mean. This r function is a wrapper function for r function rma. The term metaanalysis means an analysis of analysis.
In this chapter we show in detail how to use the statistical package stata both to perform a meta analysis and to examine the data in more detail. In this chapter, we briefly summarize the information in sutton et al. In this section you can download the metaeasy excel addin, described in the journal of statistical software click here for the paper. Metaregression is often used to explore heterogeneity induced by the relationship between moderators and study effect sizes. Pooled standardized mean difference smd with 95% ci was employed to evaluate the association of rs562556 with serum lipids levels. Apr 08, 2019 the objective of this study is to describe the general approaches to network meta analysis that are available for quantitative data synthesis using r software. As for the particular topic of combining hazard ratio studies in a meta analysis, the book by parmar and machin. However, its summary effect size, not the true effect size.
Statsdirect calls statistics for measuring heterogentiy in metaanalysis noncombinability statistics in order to help the user to interpret the results. A comprehensive set of userwritten commands is freely available for metaanalysis. In every meta analysis you start with the published summary data for each study and compute the treatment effect or effect size. Stata, one of the most commonly used software packages for meta. Raw unstandardized mean difference d standardized mean difference, d and g response ratios introduction when the studies report means and standard deviations, the preferred effect size is usually the raw mean difference, the standardized mean difference, or the response ratio. Metaanalysis of prevalence journal of epidemiology. Metaxl employs the same metaanalysis methods that can be accessed in general statistical packages such as stata and in dedicated metaanalysis software, but makes two additional methods available.
Metaanalysis of studies with binary relative risk, odds ratio, risk difference or continuous outcomes difference in means, standardised difference in means can be performed. We conducted a network meta analysis using two approaches. Methods a detailed description of various statistical procedures to perform meta analysis which can be performed with metan can be found elsewhere 10. These random effects are assumed to be normal with mean zero and variance. Metaanalytic methods for pooling rates when followup. Influence of unhealthy food and beverage marketing on. A handson practical tutorial on performing metaanalysis with stata.
Stata 16 introduces a new suite of commands for performing metaanalysis. For more advanced metaanalysis, including metaregression, i would recommend the r package metafor by wolfgang viechtbauer. See statas full list of official metaanalysis features stata users have also developed numerous excellent commands for performing metaanalyses. This effect size can only be used when all studies in the analysis used precisely the same scale. Multilevel analysis techniques and applications by joop hox.
In this article we present methods for the metaanalysis of prevalence. Look at the help file for the command that you will be using. Sterne editors watch meta analysis in stata read a brief overview of meta analysis. But i got inconsistent results from the two methods. Note, results are not backtransformed in printouts of metaanalyses using summary measures with transformations, e. This article presents a general overview of the program to serve as a starting point for users interested in performing meta analysis of proportions in stata software. Sterne editors watch metaanalysis in stata read a brief overview of metaanalysis. The command can perform fixed and random effects network metaanalysis assuming either a common or different betweenstudy variances across comparisons. Meta analysis is a statistical technique for combining the results. For this workshop, we will be using the meta analysis commands that were introduced in stata 16. Or, if a study reports means and standard deviations you might compute the. As of stata 16, stata has an official suite of meta analysis commands. Heterogeneity in metaanalysis q, isquare statsdirect. By specifying an effect size, which is the minimum difference that is worth research attention, researcher could design a study with optimal power rather than wasting resources on trivial effects.
Stata module for fixed and random effects metaanalysis, statistical software components s456798, boston college department of economics, revised 23 sep 2010. Network metaanalysis with mean difference data statalist. Multilevel analysis techniques and applications by joop hox chapter 8. Although we are in the process of completing a formal software comparison project, we are confident that the mix program can compete in many respects usability, analytical options, comprehensiveness, and export options with most of the existing metaanalysis programs like comprehensive metaanalysis, metawin, revman, or weasyma. I appreciate if anyone can tell me that how should i set the stata syntax for having the pooled mean differences in metan or db metan. The following metaanalysis commands are all described in metaanalysis in stata. A total of 7 eligible articles involving 4742 subjects were included in the final metaanalysis. Accordingly, an analytic approach called network metaanalysis nma was developed. An introduction to meta analysis in stata jonathan sterne school of social and community medicine university of bristol, uk.
The multilevel approach to meta analysis sas textbook examples the code for this chapter was provided by professor hoffman from the department of psychology of the university of nebraskalincoln. A systematic comparison of software dedicated to meta. This book provides a clear and thorough introduction to metaanalysis, the process of synthesizing data from a series of separate studies. We have developed metaprop, a new program in stata to perform. To examine empirically whether the mean difference md or the standardised mean difference smd is more generalizable and statistically powerful in meta analyses of continuous outcomes when the same unit is used. Metaanalysis has become a critically important tool in fields as diverse as medicine, pharmacology, epidemiology, education, psychology, business, and ecology. Stata users have also developed numerous excellent commands for performing meta analyses. Weighted mean or weighted mean difference bandolier. For example, if a study reports the number of events in each group you might compute the odds ratio. This site uses cookies to store information on your computer. Before you start collecting the actual data for the meta analysis, decide which statistical software package will be used to analyze the data. A handson practical tutorial on performing metaanalysis. Metaanalysis software forest plot radial plot ncss.
The raw mean difference d may be used as the effect size when the outcome scale is either inherently meaningful or well known due to widespread use. Metaanalysis of hazard ratios statistical software. These studies are assumed to have a treatment group and a control group. The model y presented in the stata program simultaneously. Knapp correction, 7 which aims to adjust for the small number of studies. For a short overview of meta analysis in medcalc, see meta analysis. Declaring the metaanalysis data is the first step of your metaanalysis in stata. Conceptually, a metaanalysis uses a statistical approach to combine the results from multiple studies in an effort to increase power over individual studies, improve estimates of the size of the effect andor to resolve uncertainty when reports disagree. Efficacy of aerobic exercise for treatment of chronic low. The goals of metaanalysis may be summarized as follows.
Glass, 1976, p3 metaanalysis techniques are needed because only. The mvmeta command in stata employs a recent approach to network metaanalysis that handles the different treatment comparisons appeared in studies as different outcomes. Chs is a coauthor of metaanalyst, hr is a coauthor of com. For dichotomous data, the metan command needs four. We address the three topics covered in the previous issues of. We address the three topics covered in the previous issues of the journal, focusing on their implementation in stata using a working example from mental health research. Wednesday 20 september 2017 introduction to metaanalysis afternoon. The purpose of this commentary is to expand on existing articles describing meta analysis interpretation,6,14,42,61 discuss differences in the results of a meta analysis based on the treatment questions, explore special cases in the use of meta analysis, and. Eight clinical cohort studies with a total of 310 clbp patients were included in the metaanalysis. See stata s full list of official meta analysis features. The historical roots of meta analysis can be traced back to 17th century studies of astronomy, while a paper published in 1904 by the statistician karl pearson in the british medical journal which collated data from several studies of typhoid inoculation is seen as the first time a meta analytic approach was used to aggregate the outcomes of multiple clinical studies.
Is useful in a meta analysis because it can combine studies of same clinical outcome using different instruments e. Meta analysis is a method to obtain a weighted average of results from various studies. As of stata 16, stata has an official suite of metaanalysis commands. Metaanalysis course software revman does not have the capacity for metaregression cma only allows one predictor in the metaregression stata, r programs more flexible 26. While stata has no intrinsic support for metaanalysis, various experts have written macros for metaanalysis, which can be downloaded from the stata web site and incorporated into stata. Is useful in a metaanalysis because it can combine studies of same clinical outcome using different instruments e. Metaanalysis quantitative and statistical approach for systematically combining results of previous research to arrive at conclusions about the body of research.
A metaanalysis is a statistical overview of the results from one or more systematic. Meta analysis is a statistical technique for combining the results from several similar studies. Metaanalysis was performed with the use of the stata statistical software. Metaanalysis has been characterized in various ways, from making order of scientific chaos to megasilliness, and has been subject of many debates. Authors of this chapter have participated in authoring several of the software packages discussed in this chapter. An updated collection from the stata journal, second edition. However, at present, nma is primarily used to mean a research effort to. The first metaanalysis showed a pooled hpvprevalence of 43% 95% ci. With each individual study, there is its observed mean, the standard deviation of observations, and the sample size. I found the comprehensive metaanalysis software program to be extremely user friendly, providing instant computational data from the simplest to the most complex statistical problems, a versatile database to help organize and restructure large volumes of multifaceted data, and parallel visuals that help better understand your data.
During this step, you specify the main information needed for metaanalysis such as the studyspecific effect sizes and their standard errors. With these three data, the metaanalysis could compute a summary effect size the summary difference in mean, and the standard deviation of the summary difference in mean. In every metaanalysis you start with the published summary data for each study and compute the treatment effect or effect size. The larger the effect size the difference between the null and alternative means is, the greater the power of a test is. Statatm is a generalpurpose, commandline driven, programmable statistical package. What is a metaanalysis in 1976, glass coined the term metaanalysis metaanalysis refers to the analysis of analyses the statistical analysis of a large collection of analysis results from individual studies for the purpose of integrating the findings.
In this article, we present procedures specific to pooling of binomial data including methods of computation of the confidence. In this chapter we show in detail how to use the statistical package stata both to perform a metaanalysis and to examine the data in more detail. Panel a displays a forest plot of the effect sizes standardized mean difference for each study and their 95% confidence intervals ci. Sensitivity analysis, residual analysis, and detection of influential studies a.
To compare among the clinical trial studies extracted for analysis, similarity in. Software technical specs comprehensive metaanalysis. A dofile, metaanalysis of test accuracy studies in stata. In this paper we provide guidance on how to undertake meta analysis using stata, one of the most commonly used software packages for meta analysis. Meta analysis of studies with binary relative risk, odds ratio, risk difference or continuous outcomes mean differences can be performed.
Metaanalysis is a statistical technique for combining the results from several similar studies. In addition to pooling effect sizes, meta analysis can also be used to estimate disease frequencies, such as incidence and prevalence. In the following sections we provide an example of fixed and random effects metaanalysis using the metan command. Aug 12, 2017 appendix b provides a detailed overview of the features of the software for meta. Stata, one of the most commonly used software packages for metaanalysis. The purpose of this commentary is to expand on existing articles describing metaanalysis interpretation,6,14,42,61 discuss differences in the results of a metaanalysis based on the treatment questions, explore special cases in the use of metaanalysis, and. Before you start collecting the actual data for the metaanalysis, decide which statistical software package will be used to analyze the data. Is the md divided by the standard deviation of the observations. For a short overview of metaanalysis in medcalc, see metaanalysis. Refer to those sources for more details about how to conduct a metaanalysis.
Saudi board of preventive medicine, riyadh ministry of health, ksa lecture 0810 dr. Outlines the role of metaanalysis in the research process shows. In addition to pooling effect sizes, metaanalysis can also be used to estimate disease frequencies, such as incidence and prevalence. The association of the pcsk9 rs562556 polymorphism with. I plan to performa meta analysis of airway volumes, and will be using the comprehensive meta analysis cma software which allows me to enter data from studies in various different formats. We have found many books and articles on metaanalysis. Moderators may include a mixture of continuous and categorical variables. The goals of meta analysis may be summarized as follows. A clear difference between the various tools is whether they are stand. The theory behind metaanalysis difference in mean statalist. In this article we present methods for the meta analysis of prevalence. May use bayesian frameworks or metaregression analysis. Each studys result may be summarized by the sample size, mean, and standard deviation for each of the two groups. Or, if a study reports means and standard deviations you might compute the standardized mean difference.
However, as we know, there could be studies that only report the mean difference comparing two treatment arms, instead of reporting individual estimates for treatment a, or placebo. In stata, a comprehensive set of userwritten commands is available for metaanalysis. We have found many books and articles on meta analysis. I know we can use the information on the sample size, mean, and sd from the interventions a, b etc. Stata module to perform meta analysis regression, statistical software components s446201, boston college department of economics, revised 05 jan 2009. An updated collection from the stata journal, second edition, which brought together all the stata journal articles about the. Can i do a metaanalysis of means, standard deviations and. In terms of a metaanalysis, sensitivity means that you get all of what you want. This is not an introduction to the use of stata software. Jun 26, 2019 stata 16 introduces a new suite of commands for performing meta analysis. However, time has taught both opponents and proponents that things are not black and white. Our objective was to compare different statistical approaches for pooling count data of varying followup times in terms of estimates of effect, precision, and clinical interpretability. An updated collection from the stata journal, second edition, which brought.
Metaanalysis in stata can be performed using the metan command. Which is more generalizable, powerful and interpretable in. Jul 12, 2004 meta analysis can be used to pool rate measures across studies, but challenges arise when followup duration varies. The standardized mean difference d or g transforms all effect.
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