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Bayesian sample size determination for cost-effectiveness studies with censored data.


ABSTRACT: Cost-effectiveness models are commonly utilized to determine the combined clinical and economic impact of one treatment compared to another. However, most methods for sample size determination of cost-effectiveness studies assume fully observed costs and effectiveness outcomes, which presents challenges for survival-based studies in which censoring exists. We propose a Bayesian method for the design and analysis of cost-effectiveness data in which costs and effectiveness may be censored, and the sample size is approximated for both power and assurance. We explore two parametric models and demonstrate the flexibility of the approach to accommodate a variety of modifications to study assumptions.

SUBMITTER: Beavers DP 

PROVIDER: S-EPMC5755783 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Bayesian sample size determination for cost-effectiveness studies with censored data.

Beavers Daniel P DP   Stamey James D JD  

PloS one 20180105 1


Cost-effectiveness models are commonly utilized to determine the combined clinical and economic impact of one treatment compared to another. However, most methods for sample size determination of cost-effectiveness studies assume fully observed costs and effectiveness outcomes, which presents challenges for survival-based studies in which censoring exists. We propose a Bayesian method for the design and analysis of cost-effectiveness data in which costs and effectiveness may be censored, and the  ...[more]

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