Total Effect refers to the overall impact of an independent variable on a dependent variable, encompassing both direct and indirect pathways. It is a fundamental concept in causal inference and mediation analysis, helping to understand the complete influence of one variable on another within a system or model.

Total Effect

overall impact

An independent variable is a factor in an experiment or study that is manipulated or controlled to observe its effect on a dependent variable. It is essential for establishing causal relationships and is typically plotted on the x-axis in graphs.

independent variable

A dependent variable is the outcome factor that researchers measure in an experiment or study, which is influenced by changes in the independent variable. It is crucial for determining the effect of the independent variable and understanding causal relationships in research settings.

dependent variable

Direct pathways

indirect pathways

Causal inference is the process of determining the cause-and-effect relationship between variables, distinguishing correlation from causation by using statistical methods and assumptions. It is crucial in fields like epidemiology, economics, and social sciences to make informed decisions and predictions based on data analysis.

causal inference

Mediation analysis is a statistical method used to understand the mechanism through which an independent variable influences a dependent variable via a mediator variable. It helps to disentangle direct and indirect effects, providing insights into the underlying causal pathways in complex relationships.

CUSTOMIZE YOUR LEARNING

CUSTOMIZE YOUR LEARNING

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