Sterne editors watch metaanalysis in stata read a brief overview of metaanalysis. Randomeffects metaanalysis evangelos kontopantelis. The actual coverage probabilities of nominal 95% confidence intervals for the treatment effect obtained using dersimonian and laird s procedure with both standard normal and t quantiles and the likelihood approach to random effects metaanalysis are shown in table 1, for n 4, 8, 16, 32 and a range of i 2 values. Here it is shown that, unless all studies are of similar size, this is inefficient when estimating the betweenstudy variance, but is remarkably efficient when estimating the treatment effect. An updated collection from the stata journal, second edition by tom m. Besides the standard dersimonian and laird approach, metaan offers a wide choice of available models. The example in this section uses the dersimonian laird method see randomeffects methods for details. Examples of the types of papers include 1 expository papers that link the use of stata commands. The most commonly used approach is the noniterative method of moments estimator proposed by dersimonian and laird. Comprehensive metaanalysis is easy to learn and use, with a clear and friendly interface. Metasoft is a free, opensource metaanalysis software tool for genomewide association study analysis, designed to perform a range of basic and advanced metaanalytic methods in an efficient manner. Randomeffects reml, ml, empirical bayes, dersimonianlaird, sidikjonkman, hedges, hunterschmidt. In stata, meta and metan commands have been developed to generate fixed and randomeffects metaanalysis. For example, brockwell et al 24 found that even with large sample sizes, the intervals based on the dersimonian and laird method did not attain the preferred coverage for the oddsratio.
To carry out random effects analysis using the approach of dersimonian and laird dsl, controlled clinical trials, 1986,7,177188 and also using that of hardy and thompsonht, statistics in medicine, 1996,15, 619629. However, it is well known that the method is suboptimal and may lead to too many statistically significant results when the number of. More tangibly, confidence intervals based on the dersimonian laird plugin style method have shown to perform poorly even when k is as large as 20 liu et al. Declaring the metaanalysis data is the first step of your metaanalysis in stata. Extending dersimonian and lairds methodology to perform. The actual coverage probabilities of nominal 95% confidence intervals for the treatment effect obtained using dersimonian and lairds procedure with both standard normal and t quantiles and the likelihood approach to random effects metaanalysis are shown in table 1, for n 4, 8, 16, 32 and a range of i 2 values. For a short overview of metaanalysis in medcalc, see metaanalysis. Note also that using the empirical bayes estimator yields the exact same results as when using the paulemandel estimator. Our antivirus check shows that this download is clean. Tests for publication bias in metaanalysis metabias 1. I n this example, we have chosen a windows installation 4. The hartungknappsidikjonkman method for random effects.
For the dersimonian and laird procedure, coverage probabilities are calculated. Stata is a generalpurpose, commandline driven, programmable statisti. While the original dersimonian and laird randomeffects model is the most widely used, it may not be the most appropriate. Sep 02, 2015 the dersimonian and laird method, currently widely used by default to estimate the between. Jacksons model is a relatively simple model for network meta. A comparison between dersimonianlaird and restricted maximum likelihood. There are many methods for estimating the heterogeneity. Especially in medical and psychological research, the by far most often used estimator is the dersimonian laird estimator dersimonian and laird 1986. Dersimonian laird, hedges, sidikjonkman, and hunterschmidt. Besides the stan dard dersimonian and laird approach, metaan offers a wide. I analyze a lot of data and, believe it or not, use the metaanalysis program every day. Part of this widespread use might be attributable to the fact that programs such as revman or comprehensive metaanalysis older versions only use this estimator. Common mistakes in meta analysis and how to avoid them.
Stata is a suite of applications used for data analysis, data management, and graphics. Our aim is to identify known methods for estimation of the between. Assessing bias some biases are peculiar to metaanalysis. Using the dersimonian laird method, the estimated heterogeneity is. Dersimonianlaird, hedges, sidikjonkman, and hunterschmidt. The procedure proposed by dersimonian and laird is efficient for the mean but not the heterogeneity parameter. Besides the stan dard dersimonian and laird approach, metaan offers a wide choice of available models.
Statacorp is a leading developer in statistical software, primarily through its flagship product stata. The sas metaanal macro ellen hertzmark and donna spiegelman may 24, 2012 abstract the %metaanal macro is a sas version 9 macro that produces the dersimonian laird estimators for random e. All data were analyzed using the updated metareg command version 2. We have now showed you how you can detect and remove extreme effect sizes outliers in your metaanalysis. In the dersimionianlaird method, the heterogeneity. To account for potential study variance, we performed a dersimonian laird randomeffects model metaanalysis of extracted data using the metan package in stata statistical software version 15. An application of metaanalysis based on dersimonian and. The most convenient way to install userwritten commands is from within stata. Nonparametric trim and fill analysis of publication bias in metaanalysis metatrim 1. Dersimonian and laird proposed an approximation method to estimate the value of. It will also download brief descriptions of all userwritten commands published in the stata technical bulletin. It is my favorite software for metaanalysis of studylevel data.
In metan, the confidence intervals are calculated using the normal distribution based on the asymptotic variance. Both binary relative risk, odds ratio, risk difference, rateratios and rate. The randomeffects method dersimonian 1986 incorporates an assumption that the different studies are estimating different, yet related, intervention effects. Association of maternal lactation with diabetes and. During this step, you specify the main information needed for metaanalysis such as the studyspecific effect sizes and their standard errors. Version 1 introduced the quality effects qe model, version 2 the inverse variance heterogeneity ivhet model, version 3 introduced the doi plot and lfk index for the detection of publication bias, version 4 added network metaanalysis. The stata newsa periodic publication containing articles on using stata and tips on using the software, announcements of new releases and updates, feature highlights, and other announcements of interest to interest to stata usersis sent to all stata users and those who request information about stata from us. In the random effects model, the weight assigned to study i is. The commonly used method for a random effects metaanalysis is the dersimonian and laird approach dl method. Aug 26, 2012 while the original dersimonian and laird randomeffects model is the most widely used, it may not be the most appropriate.
This can be accessed by downloading lfk stata package. When logodds ratio is used as a summary measure ie, common treatment effect, y k lnor k where lnor k is the logodds ratio in k th center and where. Those relating to metaanalysis can be displayed by typing search meta. Metaanalysis helps aggregate the information, often overwhelming, from many studies in a principled way into one unified final conclusion or provides the reason why such a conclusion cannot be reached. The command reports a variety of heterogeneity measures, including cochrans q, i2, h2 m, and the betweenstudies variance estimate. Dersimonianlaird statistic the dersimonian and laird statistic is based on random effects model, which obtained by. To suggest that a nonsignificant pvalue justifies the use a fixedeffect analysis is to suggest that the lack of significance proves that the null is correct that the studies all share a common effect size. Comparison of three tests of homogeneity of odds ratios in. Forestpmplot is a free, opensource a pythoninterfaced r package tool for analyzing the heterogeneous studies in metaanalysis by visualizing the. The actual developer of the program is statacorp lp. The commonly used method for a random effects metaanalysis is the dersimonian and laird approach dl method 1. Dersimonian and laird 1986 assumes that the study effect sizes are different and. As we have mentioned before, however, it is not only statistical outliers which may cause concerns regarding the robustness of our pooled effect. The procedure suggested by dersimonian and laird is the simplest and most commonly used method for fitting the random effects model for metaanalysis.
The principal summary statistic was or with 95% confidence intervals. The summary effect size can be estimated using the inverse variance method, where the study weights are. And here, logic tells us that the null is probably false. Besides the standard dersimonian and laird approach, metaan offers. The command reports a variety of heterogeneity measures. You assume responsibility for the selection of the program and for the use of results obtained from that program. The %metaanal macro is an sas version 9 macro that produces the dersimonianlaird estimators for random or fixedeffects model. Extensions of dersimonian and lairds methodology have previously been proposed for multivariate meta. Various procedures to perform metaanalysis have been implemented in the stata command metan. A variation on the inversevariance method is to incorporate an assumption that the different studies are estimating different, yet related, intervention effects. The software provides a detailed display of metaanalytic results plus a wonderful format for presentation of results. View or download all content the institution has subscribed to.
Stata module to perform fixed or randomeffects metaanalyses. Dersimonianlaird random effects model for mh approach dersimonian and laird summary or additional component d to weight. The procedure proposed by dersimonian and laird is efficient for the. May 24, 2012 the sas metaanal macro ellen hertzmark and donna spiegelman may 24, 2012 abstract the %metaanal macro is a sas version 9 macro that produces the dersimonianlaird estimators for random e. The values for the paulemandel, cochran, dersimonian laird, twostep cochran, and twostep dersimonian laird estimators are given in tables 3 and 4 in the paper and are exactly the same as given above. In stata the dersimonian and laird dl mo del is used in the most popular metaanalysis commands, the recen tly updated metan and the older but still useful meta harris et al. When asked whether you want to run the file, click on yes.
How does the dersimonian and laird procedure for random. Stata has a long history of metaanalysis methods contributed by stata researchers, for instance, palmer and sterne 2016. Raw data counts or summary data adjusted or, rr or rd can be used as input. Metaspss disclaimer metaspss is provided as is without warranty of any kind. Statsdirect first transforms proportions via the freemantukey double arcsine method murray et al.
Used by professional researchers for more than 30 years. To account for potential study variance, we performed a dersimonianlaird randomeffects model metaanalysis of extracted data using the metan package in stata statistical software version 15. As we all learned in our first statistics class, the lack of significance does not prove that the null is true. The entire risk as to the quality, performance, and fitness for intended purpose is with you. More tangibly, confidence intervals based on the dersimonianlaird plugin style method have shown to perform poorly even when k is as large as 20 liu et al. The historical roots of metaanalysis 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 metaanalytic approach was used to aggregate the outcomes of multiple clinical studies. It is the latest software in which you are able to get all the features that you want due to its multicore system supported. Previously, we showed how to perform a fixedeffectmodel metaanalysis using the metagen and metacont functions however, we can only use the fixedeffectmodel when we can assume that all included studies come from the same population. Performance of statistical methods for metaanalysis when. The metaanalysis program is easy to use and provides me with information that would be hard to get by any other means. You declare this information once by using either meta set or meta esize, and it is then used by all meta commands. This article describes the new metaanalysis command metaan, which can be used to perform fixed or randomeffects metaanalysis. Nov 10, 2014 the procedure proposed by dersimonian and laird is efficient for the mean but not the heterogeneity parameter.