Quantifying and Correcting Generalization Bias in Safety Assessment
View Presentation *Eloise Kaizar, Ohio State University Keywords: selection bias Randomized controlled trials (RCTs) are the traditional gold standard evidence for medical decision-making, including decisions regarding drug safety. However, protocols that limit enrollment eligibility introduce selection error that severely limits a RCT's applicability to a wide range of patients. This is especially problematic for broad safety assessment where the trial protocol specifically excludes those at risk of adverse events. Conversely, high quality observational data can be representative of entire populations, but freedom to choose treatment can bias estimators based on this data. However, observational data may be used to quantify the size of possible bias due to recruitment protocols. We also propose an estimator of effect size that capitalizes on RCTs' strong internal validity and observational studies' strong external validity.
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Key Dates
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April 30 - May 22, 2013
Invited Abstract Submission Open -
June 4, 2013
Online Registration Opens -
August 9 - August 23, 2013
Invited Abstract Editing -
August 23, 2013
Short Course materials due from Instructors -
August 26, 2013
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September 9, 2013
Cancellation Deadline and Registration Closes @ 11:59 pm EDT -
September 16 - September 18, 2013
Marriott Wardman Park, Washington, DC