Basics of stata this handout is intended as an introduction to stata. If you are using the official metaanalysis commands in stata 16, the collection of stata journal articles is still valuable because the collection contains information about metaanalysis, and not just information on the communitycontributed metaanalysis commands. A meta regression can be done in stata 16 with the meta regress command. The results of each study may be summarized as counts in a 2by2 table. To do the metaregression i have taken all the aspects of the included studies that could have contributed to the heterogeneity followup duration, study size, study population and period of the. This book is composed of four chapters covering a variety of topics about using stata for regression. This will include looking at the accumulation of evidence in cumulative meta analysis, using graphical and statistical techniques to look for evidence of bias, and using meta regression to investigate possible sources of heterogeneity. I want to see what this variable does to the mortality rate, expressed as rd or or. The p value of each regression coefficient will indicate whether this difference is statistically significant. How to conduct metaregression with continuous and categorial.
It has usually been performed in a bayesian setting, but recently it has become possible in a frequentist setting using multivariate meta analysis and meta regression, implemented in stata. If you are using the official meta analysis commands in stata 16, the collection of stata journal articles is still valuable because the collection contains information about meta analysis, and not just information on the communitycontributed meta analysis commands. Reprinted in stata technical bulletin reprints, vol. Data analysis with stata 12 tutorial university of texas. It also provides explanations of various plots that are presented as well as introducing metaregression. Performing standard metaregression analysis with spss.
These studies have a treatment group arm and a control group. I am conducting a metaanalysis in psychotherapy research and want to use metaregression to identify moderators. However, the output for one of the variables sample size the regression coefficient and. This is the second of two stata tutorials, both of which are based on the 12th version of stata, although most commands discussed can be used in. This r function is a wrapper function for r function rma. The command meta summarize, subgroup can be used to do a subgroup analysis. The estimated model coefficients, corresponding standard errors, and the test statistics are exactly the same. In subsequent papers in this series, we will discuss how you can conduct meta analysis of diagnostic and screening studies, and principles of network meta analyses, where you can conduct a meta analysis with more than one intervention or exposure variable.
Meta analysis of studies with binary relative risk, odds ratio, risk difference or continuous outcomes mean differences can be performed. I have often found it useful to write directly to package authors with queries about their addon packages as a package author, i myself entertain such questions frequently. We now briefly describe the four major metaregression approaches presented in the literature. This is an excellent piece of software to conduct metaregression. Stata is a software package popular in the social sciences for manipulating and summarizing data and conducting statistical analyses. Official meta analysis commands are available in stata 16 stata 16 contains a suite of commands for performing meta analysis. Introduction to metaregression analysis hendrix college. Technically, linear regression estimates how much y changes when x changes one unit. We present a revised version of the metareg command, which performs meta analysis regression meta regression on studylevel summary data. We have also made additions to the output, added an option. In stata, a comprehensive set of userwritten commands is available for metaanalysis. Impact of mechanical ventilation on the daily costs of icu.
Indeed, some argue that multiple metaregression is often improperly used and interpreted in practice, leading to a low validity of many metaregression models. Linear regression using stata princeton university. The results of the analyses were applied to a recent study calculating the excess lengthofstay associated with icuacquired ventilatorassociated pneumonia, a major complication of mechanical ventilation. The major revisions involve improvements to the estimation methods and the addition of an option to use a permutation test to estimate pvalues, including an adjustment for multiple testing we have also made additions to the output, added an. Stata module to perform metaanalysis regression metareg performs randomeffects metaregression on studylevel summary data. However, when there is substantial unaccounted heterogeneity in. This paper is a basic introduction to the process of metaanalysis. The regression coefficients will estimate how the intervention effect in each subgroup differs from a nominated reference subgroup. Metaanalyses have become an essential tool in synthesizing evidence on clinical and epidemiological questions derived from a multitude of similar studies assessing the particular issue. Metaanalysis of proportions introduction this module performs a metaanalysis of a set of twogroup, binaryevent studies. Official metaanalysis commands are available in stata 16 stata 16 contains a suite of commands for performing metaanalysis.
The major revisions involve improvements to the estimation methods and the addition of an option to use a permutation test to estimate pvalues, including an adjustment for multiple testing. Like ordinary least squares regression models, metaregression models include a single intercept and a slope for each moderator variable. Mixedeffects metaregression was performed to explore for sources of heterogeneity. This is an excellent piece of software to conduct meta regression. Metaregression is analogous to standard regression used when individual data are available, but in metaregression, the observations. Regression with stata chapter 1 simple and multiple regression. We present a revised version of the metareg command, which performs metaanalysis regression. I am working on a metaregression of a random effects metaanalysis with 53 studies.
We even can use meta regression models to analyze association between treatment effect and study characteristics. Brief overview of metaanalysis metaanalysis models commoneffect. Linear regression and the mixedeffects metaregression model. This is a revised version of the program originally written by stephen sharp stb42, sbe23. Regression with stata chapter 1 simple and multiple. I am conducting a meta analysis in psychotherapy research and want to use meta regression to identify moderators. Metaregression is a technique for performing a regression analysis to assess the relationship between the treatment effects and the study characteristics of interest e. I have undertaken a meta regression as part of a meta analysis.
It has usually been performed in a bayesian setting, but recently it has become possible in a frequentist setting using multivariate metaanalysis and metaregression, implemented in stata. Pdf we present a revised version of the metareg command, which performs metaanalysis regression metaregression on studylevel summary data. We even can use metaregression models to analyze association between treatment effect and study characteristics. When running a regression we are making two assumptions, 1 there is a linear relationship between two variables i. Note, results are not backtransformed in printouts of meta analyses using summary measures with transformations, e. Metaregression columbia university mailman school of. Meta regression is more effective at this task than are standard meta analytic techniques. The first approach is a fixed effects approach which utilizes logistic regression. Meta regression introduction fixedeffect model fixed or random effects for unexplained heterogeneity randomeffects model introduction in primary studies we use regression, or multiple regression, to assess the relationship between one or more covariates moderators and a dependent variable. Meta regression is a tool used in meta analysis to examine the impact of moderator variables on study effect size using regression based techniques. We should emphasize that this book is about data analysis and that it demonstrates how stata can be used for regression analysis, as opposed to a book that covers the.
We now briefly describe the four major meta regression approaches presented in the literature. Difference between metaregression and linear regression. It seeks to summarize and explain the disparate empirical findings routinely reported in nearly all areas of economics. For example, studies in which allocation sequence concealment was adequate may yield different results from those in which it was inadequate. Metaregression is more effective at this task than are standard metaanalytic techniques. Welcome tessa, this seems to be a stataspecific and, actually, a metaregspecific question, so i have voted to shift it to stackoverflow where stataspecific questions are usually handled. Metaprop is a statistical program implemented to perform metaanalyses of proportions in stata. The overall isquare in the meta analysis is 79% with p0. In this model, the data are y i, s i,andx i, and we aim to estimate the. Depicting estimates using the intercept in metaregression.
Note, results are not backtransformed in printouts of metaanalyses using summary measures with transformations, e. I am working on a meta regression of a random effects meta analysis with 53 studies. By the way, user wolfgang is the author of an r package called metafor. Difference between metaregression and linear regression in. A basic tutorial arindam basu university of canterbury may 12, 2017 concepts of metaanalyses meta analysis refers to a process of integration of the results of many studies to arrive at evidence syn. As we have mentioned before, multiple metaregression, while very useful when applied properly, comes with certain caveats we have to know and consider when fitting a model. This document is an introduction to using stata 12 for data analysis. Linear regression analysis in stata procedure, output and. Introduction metaregression approaches ncbi bookshelf. Openingsaving a stata datafile quick way of finding variables subsetting using conditional if stata color coding system from spsssas to stata example of a dataset in excel from excel to stata copyandpaste. This will generate the output stata output of linear regression analysis in stata. Network metaanalysis is a popular way to combine results from several studies usually randomized trials comparing several treatments or interventions. To do the meta regression i have taken all the aspects of the included studies that could have contributed to the heterogeneity followup duration, study size, study population and period of the. Like ordinary least squares regression models, meta regression models include a single intercept and a slope for each moderator variable.
How do i interpret an e in a metaregression coefficient. Although it is commonly ignored in practice, the constant, or intercept, in a meta regression equation can be extremely valuable because using it permits one to estimate confidence bands and intervals. Meta analyses have become an essential tool in synthesizing evidence on clinical and epidemiological questions derived from a multitude of similar studies assessing the particular issue. Categorical models and metaregression ryan williams former managing editor, methods coordinating group assistant professor, counseling, educational psychology, and research, university of memphis, usa campbell collaboration colloquium may 2012. Meta regression is a statistical method that can be implemented following a traditional meta analysis and can be regarded as an extension to it. Throughout, bold type will refer to stata commands, while le names, variables names, etc. We present a revised version of the metareg command, which performs metaanalysis regression metaregression on studylevel summary data.
One of these macros is called metareg which can perform fixedeffect or mixedeffects metaregression. An extension of mvmeta, my program for multivariate randome. The relative increase in the daily costs was estimated using random effects meta regression. This will include looking at the accumulation of evidence in cumulative metaanalysis, using graphical and statistical techniques to look for evidence of bias, and using metaregression to investigate possible sources of heterogeneity. If studies are divided into subgroups see section 9. The overall isquare in the metaanalysis is 79% with p0. We should emphasize that this book is about data analysis and that it demonstrates how stata can be used for regression analysis, as opposed to a book that. It is used to study the relationship between study effect sizes and covariates.
Metaprop is a statistical program implemented to perform meta analyses of proportions in stata. Linear regression and the mixedeffects metaregression. One of these macros is called metareg which can perform fixedeffect or mixedeffects meta regression. In stata, a comprehensive set of userwritten commands is available for meta analysis. Article information, pdf download for metaregression in stata, open epub for. Stata is available on the pcs in the computer lab as well as on the unix system. However, lm computes the pvalues based on the tdistribution, while rma uses by default the standard normal distribution. Although it is commonly ignored in practice, the constant, or intercept, in a metaregression equation can be extremely valuable because using it permits one to estimate confidence bands and intervals. Metaregression may be performed using the metareg macro available for the stata statistical package. Network meta analysis is a popular way to combine results from several studies usually randomized trials comparing several treatments or interventions. Although there is not heterogeneity in these data to be explained by a meta regression, an example of the command and its output is given below. For how to perform metaanalysis in stata, seemeta meta. Metaregression is a tool used in metaanalysis to examine the impact of moderator variables on study effect size using regressionbased techniques.