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Sensitivity analysis
Meta-analysis, the statistical process for combining data from multiple studies, is the basis for evidence based practice in the health sciences, social sciences, and a host of other fields. Pharmaceutical companies use meta-analysis to gain approval for new drugs. Clinicians use it to determine the most effective course of treatment. Researchers use it to plan new studies, to justify these studies (in grant applications) and to put these studies in context (in the introductory section of published papers).
In every meta-analysis you start with the published summary data for each study and compute the treatment effect (or effect size). For example, if a study reports the number of events in each group you might compute the odds ratio. Or, if a study reports means and standard deviations you might compute the standardized mean difference. With some software, this process can be tedious and difficult.
“What if I have only means, or p-values, or ...” - Start with almost any kind of data and CMA will compute the effect size for you. Enter events and sample size (as in the example shown) or means and standard eviations, or p-values, or odds ratios and confidence limits – select from more than 100 data formats.
To see the formula used to compute an effect size, simply double-click on that effect size. The program opens a dialog box that shows the computation for that specific row.
What if one study provided events and sample size, but another provided the odds ratio and confidence interval and another provided only a p-value? You can enter a different kind of data for each study. Customize the data-entry screen with as many data formats as needed. Comprehensive Meta-Analysis will compute the effect size for each study AND show you exactly how it was computed!
Run the meta-analysis with one click to display the screen shown here. Then use the menus to customize the display and computational options.
“Is the intervention more effective for one group of studies than another?” - Use weighted ANOVA to group by study type (e.g., chronic vs. acute patients). The program will run the meta-analysis within groups and compare the treatment effect across groups.
“Does the treatment effect increase with dosage?” - Use meta-regression to assess the impact of any continuous moderators.
Use a forest plot to communicate results clearly and effectively. Export it to Word and include it in papers. Export it to PowerPoint, and include it in presentations. Modify the symbols, colors, text, columns. All elements of the plot are under your control.