Välitysvaikutusmallit

Välitysvaikutusmallit, known in English as mediation effect models or simply mediation models, are statistical tools used in social sciences and psychology to understand the indirect relationship between an independent variable and a dependent variable. Instead of assuming a direct link, these models propose that the independent variable influences the dependent variable through a third, intervening variable, known as the mediator. This mediator variable acts as a bridge, explaining how and why the independent variable affects the dependent variable.

The core idea is to decompose the total effect of the independent variable into direct and indirect effects. The direct effect represents the influence of the independent variable on the dependent variable that does not go through the mediator. The indirect effect, on the other hand, is the influence that is transmitted via the mediator. When the indirect effect is statistically significant, it suggests that the mediator plays a crucial role in the relationship.

Common methods for analyzing mediation include the Baron and Kenny approach, though contemporary research often favors more robust techniques like bootstrapping. Bootstrapping estimates the indirect effect by resampling the data and calculating the product of the coefficients representing the path from the independent variable to the mediator and the path from the mediator to the dependent variable. This method provides confidence intervals for the indirect effect, allowing researchers to assess its statistical significance. Understanding mediation is vital for developing effective interventions, as it identifies specific pathways that can be targeted for change.