Single Proxy Control

Details

• Personal Author:
  Park C ; Richardson DB ; Tchetgen Tchetgen EJ
• Description:
  Negative control variables are sometimes used in nonexperimental studies to detect the presence of confounding by hidden factors. A negative control outcome (NCO) is an outcome that is influenced by unobserved confounders of the exposure effects on the outcome in view, but is not causally impacted by the exposure. Tchetgen Tchetgen (2013) introduced the Control Outcome Calibration Approach (COCA) as a formal NCO counterfactual method to detect and correct for residual confounding bias. For identification, COCA treats the NCO as an error-prone proxy of the treatment-free counterfactual outcome of interest, and involves regressing the NCO on the treatment-free counterfactual, together with a rank-preserving structural model, which assumes a constant individual-level causal effect. In this work, we establish nonparametric COCA identification for the average causal effect for the treated, without requiring rank-preservation, therefore accommodating unrestricted effect heterogeneity across units. This nonparametric identification result has important practical implications, as it provides single-proxy confounding control, in contrast to recently proposed proximal causal inference, which relies for identification on a pair of confounding proxies. For COCA estimation we propose 3 separate strategies: (1) an extended propensity score approach, (2) an outcome bridge function approach, and (3) a doubly-robust approach. Finally, we illustrate the proposed methods in an application evaluating the causal impact of a Zika virus outbreak on birth rate in Brazil. [Description provided by NIOSH]
• Subjects:
  Occupational Health Safety
• Keywords:
  Analytical Processes Author Keywords: Confounding Proxy Bioinformatics Doubly Robust Exposure Assessment Extended Propensity Score Negative Controls Statistical Quality Control Unmeasured Confounding
• ISSN:
  0006-341X
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Journal Article
• Place as Subject:
  California ; North Carolina ; OSHA Region 3 ; OSHA Region 4 ; OSHA Region 9 ; Pennsylvania
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Volume:
  80
• Issue:
  2
• NIOSHTIC Number:
  nn:20069582
• Citation:
  Biometrics 2024 Jun; 80(2):ujae027
• Contact Point Address:
  Chan Park, Department of Statistics and Data Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104
• Email:
  chanpk@wharton.upenn.edu
• Federal Fiscal Year:
  2024
• Performing Organization:
  University of North Carolina-Chapel Hill
• Peer Reviewed:
  True
• Start Date:
  20190801
• Source Full Name:
  Biometrics
• End Date:
  20220731
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:0b5be44529c1c6fd60b64c25de1def2c86a60736a9f10d049e88e7ed5b5d18d18256b929a74ae5b4b8de2345522479230eb3466576d32fa1d9c8e3e92bc07126
• Download URL:
  https://stacks.cdc.gov/view/cdc/207989/cdc_207989_DS1.pdf
• File Type:
  [PDF - 853.39 KB ]