Nonparametric Bounds for the Risk Function.

Journal Article (Journal Article)

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.

Full Text

Duke Authors

Cited Authors

  • Cole, SR; Hudgens, MG; Edwards, JK; Brookhart, MA; Richardson, DB; Westreich, D; Adimora, AA

Published Date

  • April 1, 2019

Published In

Volume / Issue

  • 188 / 4

Start / End Page

  • 632 - 636

PubMed ID

  • 30698633

Pubmed Central ID

  • PMC6438811

Electronic International Standard Serial Number (EISSN)

  • 1476-6256

Digital Object Identifier (DOI)

  • 10.1093/aje/kwz013


  • eng

Conference Location

  • United States