![]() ![]() Based on this information, a meta-regression model tries to predict \(y\), the study’s effect size. ![]() The variable \(x\) represents characteristics of studies, for example the year in which it was conducted. In meta-regression, this logic is applied to entire studies. Usually, regression models are based on data comprising individual persons or specimens, for which both the value of \(x\) and \(y\) is measured. In its simplest form, a regression model tries to use the value of some variable \(x\) to predict the value of another variable \(y\). Regression analysis is one of the most common statistical methods and used in various disciplines. It is very likely that you have heard the term “regression” before. We also mentioned that subgroup analyses are a special form of meta-regression. Instead, they allow us to investigate patterns of heterogeneity in our data, and what causes them. As we learned, subgroup analyses shift the focus of our analyses away from finding one overall effect. N the last chapter, we added subgroup analyses as a new method to our meta-analytic “toolbox”. ![]()
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