Bayesian methods in decision analysis.

1971 ◽  
Author(s):  
Jacques P. Pezier
Keyword(s):  
Decision Analysis ◽  
Bayesian Methods

Bayesian Applications in Auditory Research

2019 ◽  
Vol 62 (3) ◽  
pp. 577-586 ◽  
Author(s):  
Garnett P. McMillan ◽  
John B. Cannon
Keyword(s):  
Monte Carlo ◽  
Markov Chain ◽  
Bayesian Methods ◽  
Prior Distribution ◽  
Interim Analysis ◽  
Iterative Process ◽  
Bayes Theorem ◽  
Sound Therapy ◽  
The Many ◽  
Auditory Research

Purpose This article presents a basic exploration of Bayesian inference to inform researchers unfamiliar to this type of analysis of the many advantages this readily available approach provides. Method First, we demonstrate the development of Bayes' theorem, the cornerstone of Bayesian statistics, into an iterative process of updating priors. Working with a few assumptions, including normalcy and conjugacy of prior distribution, we express how one would calculate the posterior distribution using the prior distribution and the likelihood of the parameter. Next, we move to an example in auditory research by considering the effect of sound therapy for reducing the perceived loudness of tinnitus. In this case, as well as most real-world settings, we turn to Markov chain simulations because the assumptions allowing for easy calculations no longer hold. Using Markov chain Monte Carlo methods, we can illustrate several analysis solutions given by a straightforward Bayesian approach. Conclusion Bayesian methods are widely applicable and can help scientists overcome analysis problems, including how to include existing information, run interim analysis, achieve consensus through measurement, and, most importantly, interpret results correctly. Supplemental Material https://doi.org/10.23641/asha.7822592

84: A Decision Analysis of Treatments for Nonobstructive Azoospermia Associated with Varicocele

2007 ◽  
Vol 177 (4S) ◽  
pp. 29-30
Author(s):  
Richard Lee ◽  
Mark A. Callahan ◽  
Glen Schattman ◽  
Philip S. Li ◽  
Marc Goldstein ◽  
...  
Keyword(s):  
Decision Analysis ◽  
Nonobstructive Azoospermia

Bayesian Methods Interpret Data Better

2012 ◽  
Author(s):  
John K. Kruschke
Keyword(s):  
Bayesian Methods

Performance of MAP-Bayesian methods for managing loss of metabolite samples in PET ligand studies

2005 ◽  
Vol 25 (1_suppl) ◽  
pp. S627-S627
Author(s):  
Mary E Spilker ◽  
Gjermund Henriksen ◽  
Till Sprenger ◽  
Michael Valet ◽  
Isabelle Stangier ◽  
...  
Keyword(s):  
Bayesian Methods

Automated Development of Clinical Strategies Using Multistage Decision Analysis

1986 ◽  
Vol 25 (04) ◽  
pp. 207-214 ◽  
Author(s):  
P. Glasziou
Keyword(s):  
Decision Tree ◽  
Decision Analysis ◽  
Decision Trees ◽  
Optimal Strategy ◽  
Cholestatic Jaundice ◽  
Clinical Strategies ◽  
Simultaneous Study

SummaryThe development of investigative strategies by decision analysis has been achieved by explicitly drawing the decision tree, either by hand or on computer. This paper discusses the feasibility of automatically generating and analysing decision trees from a description of the investigations and the treatment problem. The investigation of cholestatic jaundice is used to illustrate the technique.Methods to decrease the number of calculations required are presented. It is shown that this method makes practical the simultaneous study of at least half a dozen investigations. However, some new problems arise due to the possible complexity of the resulting optimal strategy. If protocol errors and delays due to testing are considered, simpler strategies become desirable. Generation and assessment of these simpler strategies are discussed with examples.

Sign in / Sign up

Export Citation Format

Share Document