Reweighting UK Biobank corrects for pervasive selection bias due to volunteering
Tinbergen Institute · Vrije Universiteit Amsterdam · +3 more institutions
Abstract
Biobanks typically rely on volunteer-based sampling. This results in large samples (power) at the cost of representativeness (bias). The problem of volunteer bias is debated. Here, we (i) show that volunteering biases associations in UK Biobank (UKB) and (ii) estimate inverse probability (IP) weights that correct for volunteer bias in UKB.
Drawing on UK Census data, we constructed a subsample representative of UKB's target population, which consists of all individuals invited to participate. Based on demographic variables shared between the UK Census and UKB, we estimated IP weights (IPWs) for each UKB participant. We compared 21 weighted and unweighted bivariate associations between these demographic variables to assess volunteer bias.
Citation impact
- FWCI
- 55.49
- Percentile
- 100%
- References
- 32
Authors
5- SVSjoerd van AltenCorresponding
Tinbergen Institute, Vrije Universiteit Amsterdam
- BWBenjamin W. Domingue
Stanford University
- JDJessica D. Faul
University of Michigan
- TJT. J. Galama
University of Southern California, Tinbergen Institute, Vrije Universiteit Amsterdam
- ATAndries T. Marees
Vrije Universiteit Amsterdam
Topics & keywords
- Biobank
- Selection bias
- Selection (genetic algorithm)
- Medicine
- Computer science
- Biology
- Bioinformatics
- Artificial intelligence