Making better decisions with imperfect data: integrating causal bias analysis into cost-effectiveness research
Client :
Liquid Themes
Making better decisions with imperfect data: integrating causal bias analysis into cost-effectiveness research
Project summary
I will incorporate causal bias analysis into cost-effectiveness analysis thereby helping better identify when plausible biases (confounding, selection bias) can easily change decisions and when decisions are robust to bias. These methods will be applied to the cost-effectiveness of total knee replacement, perfusion MRI and interventions on BMI.
More detailed information
Principal Investigator:
Dr. Jeremy Labrecque
Role Erasmus MC:
Principal Investigator
Department:
Project website:
Funding Agency:
NWO