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This module will introduce the basic concepts of graphical models focusing on their use in causal inference as applied in epidemiological and biostatistical research. Causal graphs aim to encapsulate the key dependencies believed to be present between variables observed in a multivariable study setting. Such graphs assist the researcher in formulating appropriate statistical methods for estimating key causal quantities of interest, and guide them into the appropriate form of statistical adjustment for confounding. This module will demonstrate the use of causal graphs and the accompanying analyses in different settings. Participants will learn how to construct analysis based on causal graph structures.