Causal Machine Learning Methods and Use of Cross‐Fitting in Settings With High‐Dimensional Confounding
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DOI: 10.1002/sim.70272
Abstract: Observational epidemiological studies commonly seek to estimate the causal effect of an exposure on an outcome. Adjustment for potential confounding bias in modern studies is challenging due to the presence of high‐dimensional confounding, which occurs… read more here.
Keywords: cross fitting; confounding; high dimensional; settings high ... See more keywords