What technique allows you to investigate a relationship while controlling for other variables?

Regression analysis is the technique that enables the investigation of relationships between variables while controlling for other factors. This is particularly important in psychological research, where multiple variables often influence an outcome.

In regression analysis, a researcher can assess how well one or more independent variables predict a dependent variable while holding other variables constant. This means that the impact of those other variables is accounted for, allowing a clearer understanding of the specific relationship between the primary variables of interest. For example, in examining the effect of therapy on anxiety reduction, regression analysis can control for variables such as age, gender, and previous mental health history, thus isolating the effect of therapy itself.

Other techniques like correlation analysis primarily assess the strength and direction of a relationship but do not control for confounding variables. T-tests compare means between two groups but do not account for additional variables affecting those means. Meta-analysis combines findings from multiple studies but is not a method for directly controlling for variables within a singular dataset. Hence, regression analysis stands out as the most appropriate technique for the task described.