Bias due to participant overlap in two‐sample Mendelian randomization
University of Cambridge · University of Bristol · +1 more institution
Abstract
Mendelian randomization analyses are often performed using summarized data. The causal estimate from a one-sample analysis (in which data are taken from a single data source) with weak instrumental variables is biased in the direction of the observational association between the risk factor and outcome, whereas the estimate from a two-sample analysis (in which data on the risk factor and outcome are taken from non-overlapping datasets) is less biased and any bias is in the direction of the null. When using genetic consortia that have partially overlapping sets of participants, the direction and extent of bias are uncertain. In this paper, we perform simulation studies to investigate the magnitude of bias and…
Citation impact
- FWCI
- 41.77
- Percentile
- 100%
- References
- 66
Authors
3Topics & keywords
- Mendelian randomization
- Statistics
- Sample size determination
- Outcome (game theory)
- Type I and type II errors
- Sample (material)
- Sampling bias
- Instrumental variable