Adjusting for unmeasured confounding using validation data

Simplified two-stage calibration for survival and dichotomous outcomes

Vidar Hjellvik, Marie L De Bruin, Sven O Samuelsen, Øystein Karlstad, Morten Andersen, Jari Haukka, Peter Vestergaard, Frank de Vries, Kari Furu

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

In epidemiology, one typically wants to estimate the risk of an outcome associated with an exposure after adjusting for confounders. Sometimes, outcome and exposure and maybe some confounders are available in a large data set, whereas some important confounders are only available in a validation data set that is typically a subset of the main data set. A generally applicable method in this situation is the two-stage calibration (TSC) method. We present a simplified easy-to-implement version of the TSC for the case where the validation data are a subset of the main data. We compared the simplified version to the standard TSC version for incidence rate ratios, odds ratios, relative risks, and hazard ratios using simulated data, and the simplified version performed better than our implementation of the standard version. The simplified version was also tested on real data and performed well.

Original languageEnglish
JournalStatistics in Medicine
Volume38
Issue number15
Pages (from-to)2719-2734
ISSN0277-6715
DOIs
Publication statusPublished - 10. Jul 2019

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Confounding
Calibration
Odds Ratio
Epidemiology
Subset
Relative Risk
Incidence
Large Data Sets
Hazard
Datasets
Estimate

Keywords

  • bias correction
  • epidemiology
  • two-stage calibration
  • unmeasured confounding
  • validation data

Cite this

Hjellvik, Vidar ; De Bruin, Marie L ; Samuelsen, Sven O ; Karlstad, Øystein ; Andersen, Morten ; Haukka, Jari ; Vestergaard, Peter ; de Vries, Frank ; Furu, Kari. / Adjusting for unmeasured confounding using validation data : Simplified two-stage calibration for survival and dichotomous outcomes. In: Statistics in Medicine. 2019 ; Vol. 38, No. 15. pp. 2719-2734.
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Hjellvik, V, De Bruin, ML, Samuelsen, SO, Karlstad, Ø, Andersen, M, Haukka, J, Vestergaard, P, de Vries, F & Furu, K 2019, 'Adjusting for unmeasured confounding using validation data: Simplified two-stage calibration for survival and dichotomous outcomes', Statistics in Medicine, vol. 38, no. 15, pp. 2719-2734. https://doi.org/10.1002/sim.8131

Adjusting for unmeasured confounding using validation data : Simplified two-stage calibration for survival and dichotomous outcomes. / Hjellvik, Vidar; De Bruin, Marie L; Samuelsen, Sven O; Karlstad, Øystein; Andersen, Morten; Haukka, Jari; Vestergaard, Peter; de Vries, Frank; Furu, Kari.

In: Statistics in Medicine, Vol. 38, No. 15, 10.07.2019, p. 2719-2734.

Research output: Contribution to journalJournal articleResearchpeer-review

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T1 - Adjusting for unmeasured confounding using validation data

T2 - Simplified two-stage calibration for survival and dichotomous outcomes

AU - Hjellvik, Vidar

AU - De Bruin, Marie L

AU - Samuelsen, Sven O

AU - Karlstad, Øystein

AU - Andersen, Morten

AU - Haukka, Jari

AU - Vestergaard, Peter

AU - de Vries, Frank

AU - Furu, Kari

N1 - © 2019 John Wiley & Sons, Ltd.

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