Assessing Evidence Inconsistency in Mixed Treatment Comparisons
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Abstract
Randomized comparisons among several treatments give rise to an incomplete-blocks structure known as mixed treatment comparisons (MTCs). To analyze such data structures, it is crucial to assess whether the disparate evidence sources provide consistent information about the treatment contrasts. In this article we propose a general method for assessing evidence inconsistency in the framework of Bayesian hierarchical models. We begin with the distinction between basic parameters, which have prior distributions, and functional parameters, which are defined in terms of basic parameters. Based on a graphical analysis of MTC structures, evidence inconsistency is defined as a relation between a functional parameter…
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Topics
Keywords
- Consistency (knowledge bases)
- Computer science
- Markov chain Monte Carlo
- Bayesian probability
- Set (abstract data type)
- Econometrics
- Statistics
- Data mining
UN Sustainable Development Goals
- Peace, Justice and strong institutions
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