In an epidemiological setting, a collider is a variable that is caused by both the exposure and the outcome of interest. The term ‘collider’ refers to the fact that, in a DAG, arrow heads showing directional associations from the two exposure and outcome variables collide into a third variable (the collider).

Adjusting for a collider in any epidemiological setting can induce an association between the exposure and outcome (see collider bias). In an MR context, collider bias can be induced if adjusting for a collider (e.g., the exposure would be a collider of the genetic instrument and confounding factors).

## References

## Other terms in 'Sources of bias and limitations in MR':

- Assortative mating
- Canalization
- Collider bias
- Confounding
- Dynastic effects
- Exclusion restriction assumption
- Harmonization failure (in two-sample MR)
- Homogeneity Assumption
- Horizontal Pleiotropy
- Independence assumption
- InSIDE assumption (in two-sample MR using aggregate data)
- Monotonicity assumption
- MR for testing critical or sensitive periods
- MR for testing developmental origins
- No effect modification assumption (Additional IV assumption)
- Non-linear effects
- Non-overlapping samples (in two-sample MR)
- Overfitting
- Pleiotropy
- Population stratification
- Regression dilution bias (attenuation by errors)
- Relevance assumption
- Reverse causality
- Same underlying population (in two-sample MR)
- Statistical power/efficiency
- Vertical Pleiotropy
- Weak instrument bias
- Winner's curse