How do I prevent omitted variable bias from interfering with research?
Omitted variable bias is common in linear regression as it’s usually not possible to include all relevant variables in the model. You can mitigate the effects of omitted variable bias by:
- Introducing control variables
- Introducing proxy variables
Using logic to predict whether you have overestimated or underestimated the effect of the variable(s) included in your regression model