A meta-analysis is used when
Meta-analysis is the statistical procedure for combining data from multiple studies. When the treatment effect (or effect size) is consistent from one study to the next, meta-analysis can be used to identify this common effect. 1 Selection of a meta-regression statistical model: e.g. simple regression, fixed-effect meta-regression or random-effect meta-regression. 2  Meta-regression is a tool used in meta-analysis to examine the impact of moderator variables on study effect size using regression-based techniques. The basic tenet of a meta-analysis is that there is a common truth behind all conceptually similar studies, but which has been measured with a certain error within individual studies. 1 Meta-regression is a tool used in meta-analysis to examine the impact of moderator variables on study effect size using regression-based techniques. 2  Meta-regression is more effective at this task than are standard regression techniques. The aim in meta-analysis then is to use approaches from statistics to derive a pooled estimate closest to the unknown common truth based on how this error is perceived. Meta-analyses are often, but not always, important components of a systematic review procedure. For instance, a meta-analysis may be conducted on several clinical trials of a medical treatment, in an effort to obtain a better understanding of how well the treatment works. 1 The standardised mean effect size is basically computed as the difference score divided by the standard deviation of the scores. 2  In meta-analysis, effect sizes should also be reported with: 3  the number of studies and the number of effects used to create the estimate. 1 In meta-analysis, effect sizes should also be reported with: 2  the number of studies and the number of effects used to create the estimate. 3  confidence intervals to help readers determine the consistency and reliability of the mean estimated effect size. When the treatment effect (or effect size) is consistent from one study to the next, meta-analysis can be used to identify this common effect. When the effect varies from one study to the next, meta-analysis may be used to identify the reason for the variation. The sensitivity analysis thus shows that the results from this meta-analysis are robust to the choice of the statistical method and to the exclusion of trials of poorer quality or of studies stopped early.
Meta-analysis to examine the impact of moderator variables on study effect size using regression-based techniques. 