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. 2019 Apr 1;188(4):632-636.
doi: 10.1093/aje/kwz013.

Nonparametric Bounds for the Risk Function

Stephen R Cole  1 , Michael G Hudgens  2 , Jessie K Edwards  1 , M Alan Brookhart  1   3 , David B Richardson  1 , Daniel Westreich  1 , Adaora A Adimora  1   4
Affiliations

Nonparametric Bounds for the Risk Function

Stephen R Cole et al. Am J Epidemiol. .

Abstract

Nonparametric bounds for the risk difference are straightforward to calculate and make no untestable assumptions about unmeasured confounding or selection bias due to missing data (e.g., dropout). These bounds are often wide and communicate uncertainty due to possible systemic errors. An illustrative example is provided.

Keywords: bias; bounds; inference; missing data.

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Figures

Figure 1.
Figure 1.
Difference in risk of acquired immune deficiency syndrome diagnosis or death from any cause by injection drug use, as a function of time on study, Women’s Interagency HIV Study, United States, 1995–2006. Crude results (A); bounds for confounding and selection bias (B). Black line or area is the point or set estimate, and gray area is the 95% confidence interval. HIV, human immunodeficiency virus.
See this image and copyright information in PMC

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