What is it about?
Current approaches to modeling crossover trials in two treatments are critically reviewed from the perspective of the practical requirements of the drug developer. Frequentist and Bayesian alternatives to approaches currently advocated are considered and compared. It is concluded that it is crucial for the applied statistician working in this field to have an appreciation of the practical medical and pharmacological background.
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Why is it important?
Grieve presents a Bayesian approach and Senn presents a frequentist one and each comments on the other's approach.
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This page is a summary of: Estimating treatment effects in clinical crossover trials, Journal of Biopharmaceutical Statistics, January 1998, Taylor & Francis,
DOI: 10.1080/10543409808835233.
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