Equally important, Stata requires that data for all studies be entered using the same format. By contrast, CMA allows you to enter data in more than 100 formats, and will compute the effect size and variance for all of these formats.
![revman 5 meta-regression revman 5 meta-regression](https://i.ytimg.com/vi/uLDbJixeQmY/maxresdefault.jpg)
If any studies provide data in another format you would need to compute the effect sizes and variances manually or by writing code. Stata will accept summary data in only three formats – events and sample size, means and standard deviations, or (in some cases) point estimate and confidence interval. CMA is a menu-driven program, similar to Excel™. Stata is a command-driven language, which means that you type commands, or use a dialog box to create commands, which are then submitted to the program. Since the functionality of Stata and CMA are comparable, the main difference is in ease of use and in the options for customizing the output. These macros include procedures for basic analysis, for cumulative analysis, for meta-regression, for publication bias, and more. While Stata has no intrinsic support for meta-analysis, various experts have written macros for meta-analysis, which can be downloaded from the Stata web site and incorporated into Stata. Stata is a general purpose statistical package. As such, it includes functions to automatically compute effect sizes, to perform basic and advanced meta-analyses, and to create publication quality graphics. NEXT: StataĬMA is a program developed specifically for meta-analysis. CMA offers additional options as well, but includes a button to "Use the same options as Revman," which sets all options to match Revman. CMA includes all of the same computational formulas, has been validated against Revman and provides exactly the same results (see documentation). The development team for CMA includes some of the same people responsible for the development of Revman. Does CMA offer the same formulas as Revman? It will also run a one-study removed analysis to show the impact of each study on the combined effect. CMA will run a cumulative meta-analysis to show how the evidence has shifted over time. To assess the potential impact of publication bias CMA includes an array of functions including a funnel plot, where Revman includes only the funnel plot. Use meta-regression to assess the impact of continuous moderators (“Does the treatment effect increase with dosage?”). Use analysis of variance to compare the treatment effect across groups (“Is the treatment more effective for acute patients than for chronic patients?”). Advanced FunctionsĬMA allows you to assess the impact of moderator variables. CMA also allows one-click export to other programs such as PowerPoint™ and Word™.
REVMAN 5 META REGRESSION FULL
By contrast, CMA allows the user full control over all elements in the forest plot, will create scalable plots (that print at the highest resolution possible for the printer or journal), and allows the user to control the color for every element on the plot. The forest plot in Revman offers few options for customization. CMA is able to create a customized, high-resolution forest plot. CMA also supports a much wider range of effect sizes than Revman.
![revman 5 meta-regression revman 5 meta-regression](https://qeios-uploads.s3.eu-west-1.amazonaws.com/editor/jNmQyu4QYnEFaE7wOcNXrdEBNasAL2Tc9QUISZj7.png)
By contrast, with CMA you can enter data for each study in its own format, and use as many formats as needed in the same analysis. Equally important, Revman requires that data for all studies be entered using the same format.
![revman 5 meta-regression revman 5 meta-regression](https://els-jbs-prod-cdn.jbs.elsevierhealth.com/cms/asset/19ca4f06-f83e-40db-87a6-8289ee4b7392/gr1.jpg)
If any studies provide data in another format (such as odds ratio and confidence intervals) you would need to compute the effect sizes and variances manually for those studies. Revman will accept summary data in only two formats – events and sample size, or means and standard deviations. Or, if a study reports means and standard deviations you might compute the standardized mean difference. For example, if a study reports the number of events in each group you might compute the odds ratio. In every meta-analysis you start with the published summary data for each study and compute the treatment effect (or effect size). CMA will compute the effect sizes automatically. By contrast, the data entry process in Revman requires the user to set up tables and comparisons before starting data entry. The mechanics of data entry are much simpler in CMA – you work with a spreadsheet interface, and can copy-and paste-data as easily as you could in Excel.