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Chunk #19 — Methods — Measures — Candidate confounders.

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Principal Component Analysis Reduces Collider Bias in Polygenic Score Effect Size Estimation.
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Candidate confounding data were selected as part of a larger study on marital status and substance use (Thomas et al., 2021). The candidate confounding data available from this study include typical covariates such as sex, generational cohort, and age, as well as measures of externalizing and internalizing behavior, romantic relationship behaviors, parental marital quality, and parental alcohol use. A summary of the candidate confounding variables that were considered and retained in the PCA for TOB and EDU are available in Supplemental Table I, Supplemental Table II, and Supplemental Table III (TOB) and Supplemental Table V, Supplemental Table VI, and Supplemental Table VII (EDU). Lifetime measures were calculated where multiple observations over time were available by taking the maximum value, or, for age of onset variables, the minimum value.