Journal
CONTEMPORARY CLINICAL TRIALS
Volume 29, Issue 5, Pages 751-755Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.cct.2008.05.007
Keywords
Bayesian enthusiastic prior; monitor; multivariate probit model; non-informative prior; skeptical prior
Funding
- national MS society
Ask authors/readers for more resources
We propose a Bayesian approach to monitor clinical trials with clustered binary outcomes using multivariate probit models. Our monitoring is based on the calculated probability of the reduced incidence rate using a new treatment compared with the standard treatment greater than a target improvement under different prior scenarios for the treatment effect. We develop a Bayesian sampling algorithm for posterior inference allowing missing values in the outcomes. We illustrate our method using a published early trail of inhaled nitric oxide therapy ill premature infants. (C) 2008 Elsevier Inc. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available