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. Author manuscript; available in PMC: 2022 Feb 3.
Published in final edited form as: Biometrics. 2019 May 5;75(3):745–756. doi: 10.1111/biom.13053

FIGURE 1.

FIGURE 1

Causal graphs of the mediation models. A, Traditional mediation analysis where the exposure influences the biomarkers. B, Latent-variable mediation analysis where the exposure influences a set of q latent, or unmeasured, factors and those factors influence both the biomarkers and the outcome. To simplify the figure, we highlight the arrows and notation for only a single factor. In the sparse scenario, we expect most effects to be 0 (i.e., λ, βEY, and βFY, are usually 0). We define the p × q matrix, Λ, so that the m, jth entry is λmj