13,348 research outputs found
Feasible Joint Posterior Beliefs
We study the set of possible joint posterior belief distributions of a group
of agents who share a common prior regarding a binary state, and who observe
some information structure. For two agents we introduce a quantitative version
of Aumann's Agreement Theorem, and show that it is equivalent to a
characterization of feasible distributions due to Dawid et al. (1995). For any
number of agents, we characterize feasible distributions in terms of a
"no-trade" condition. We use these characterizations to study information
structures with independent posteriors. We also study persuasion problems with
multiple receivers, exploring the extreme feasible distributions.Comment: 51 page
Feasible Joint Posterior Beliefs
We study the set of possible joint posterior belief distributions of a group of agents who share a common prior regarding a binary state and who observe some information structure. Our main result is that, for the two agent case, a quantitative version of Aumann's Agreement Theorem provides a necessary and sufficient condition for feasibility. For any number of agents, a related "no trade" condition likewise provides a characterization of feasibility. We use our characterization to construct joint belief distributions in which agents are informed regarding the state, and yet receive no information regarding the other's posterior. We study a related class of Bayesian persuasion problems with a single sender and multiple receivers, and explore the extreme points of the set of feasible distributions
Feasible Joint Posterior Beliefs
We study the set of possible joint posterior belief distributions of a group of agents who share a common prior regarding a binary state and who observe some information structure. Our main result is that, for the two agent case, a quantitative version of Aumann's Agreement Theorem provides a necessary and sufficient condition for feasibility. For any number of agents, a related "no trade" condition likewise provides a characterization of feasibility. We use our characterization to construct joint belief distributions in which agents are informed regarding the state, and yet receive no information regarding the other's posterior. We study a related class of Bayesian persuasion problems with a single sender and multiple receivers, and explore the extreme points of the set of feasible distributions
Implementing the EffTox dose-finding design in the Matchpoint trial
Background: The Matchpoint trial aims to identify the optimal dose of ponatinib to give with conventional
chemotherapy consisting of fludarabine, cytarabine and idarubicin to chronic myeloid leukaemia patients in blastic
transformation phase. The dose should be both tolerable and efficacious. This paper describes our experience
implementing EffTox in the Matchpoint trial.
Methods: EffTox is a Bayesian adaptive dose-finding trial design that jointly scrutinises binary efficacy and toxicity
outcomes. We describe a nomenclature for succinctly describing outcomes in phase I/II dose-finding trials. We use
dose-transition pathways, where doses are calculated for each feasible set of outcomes in future cohorts. We introduce
the phenomenon of dose ambivalence, where EffTox can recommend different doses after observing the same
outcomes. We also describe our experiences with outcome ambiguity, where the categorical evaluation of some
primary outcomes is temporarily delayed.
Results: We arrived at an EffTox parameterisation that is simulated to perform well over a range of scenarios. In
scenarios where dose ambivalence manifested, we were guided by the dose-transition pathways. This technique
facilitates planning, and also helped us overcome short-term outcome ambiguity.
Conclusions: EffTox is an efficient and powerful design, but not without its challenges. Joint phase I/II clinical trial
designs will likely become increasingly important in coming years as we further investigate non-cytotoxic treatments
and streamline the drug approval process. We hope this account of the problems we faced and the solutions we used
will help others implement this dose-finding clinical trial design.
Trial registration: Matchpoint was added to the European Clinical Trials Database (2012-005629-65) on 2013-12-30
Common Agency and the Revelation Principle
In the common agency problem multiple mechanism designer simultaneously attempt to control the behavior of a single privately informed agent. The paper shows that the allocations associated with equilibria relative to any ad hoc set of fessible mechanisms can be reproduce as equilibria relative to (some subset of) the set of menus. Furthermore, equilibria relative to the set of menus are weakly robust in the sense that it is possible to find continuation equilibria so that the equilibrium allocations persist even when the set of feasible mechanisms is enlarged.
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