CHICAGO -- A study comparing different statistical methods used to remove the effects of selection bias in observational studies finds that results may vary and caution may be warranted when ...

• Accounting for bias is a major challenge confronting the use of observational data to gain important insights into real-world treatment effects. • No single study design will satisfy all information ...

• Heterogeneity in treatment effects is likely to be ubiquitous, and the failure to detect it represents a failure of science. • Hidden heterogeneity often leads to misleading results from randomized ...