Bounding Formulas for Selection Bias
Tzu-Hsuan Huang, Wen‐Chung Lee
Abstract
Open-access reader
Tzu-Hsuan Huang, Wen‐Chung Lee
Abstract
Open-access reader
Researchers conducting observational studies need to consider 3 types of biases: selection bias, information bias, and confounding bias. A whole arsenal of statistical tools can be used to deal with information and confounding biases. However, methods for addressing selection bias and unmeasured confounding are less developed. In this paper, we propose general bounding formulas for bias, including selection bias and unmeasured confounding. This should help researchers make more prudent interpretations of their (potentially biased) results.
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Researchers conducting observational studies need to consider 3 types of biases: selection bias, information bias, and confounding bias. A whole arsenal of statistical tools can be used to deal with information and confounding biases. However, methods for addressing selection bias and unmeasured confounding are less developed. In this paper, we propose general bounding formulas for bias, including selection bias and unmeasured confounding. This should help researchers make more prudent interpretations of their (potentially biased) results.
Key concepts: Confounding, Selection bias, Bounding overwatch, Information bias, Observational study, Selection (genetic algorithm), Econometrics, Statistics