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The Sign of the Bias of Unmeasured Confounding
Author(s) -
VanderWeele Tyler J.
Publication year - 2008
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.1541-0420.2007.00957.x
Subject(s) - confounding , observational study , sign (mathematics) , omitted variable bias , information bias , outcome (game theory) , econometrics , variable (mathematics) , causal inference , instrumental variable , statistics , selection bias , mathematics , mathematical economics , mathematical analysis
Summary Unmeasured confounding variables are a common problem in drawing causal inferences in observational studies. A theorem is given which in certain circumstances allows the researcher to draw conclusions about the sign of the bias of unmeasured confounding. Specifically, it is possible to determine the sign of the bias when monotonicity relationships hold between the unmeasured confounding variable and the treatment, and between the unmeasured confounding variable and the outcome. Some discussion is given to the conditions under which the theorem applies and the strengths and limitations of using the theorem to assess the sign of the bias of unmeasured confounding.