Abstract Number:
3113
Submission Type:
Contributed Abstract
Contributed Abstract Type:
Paper
Participants:
Mark Meyer (1), Amia Graye (2), Kimberly Sellers (3)
Institutions:
(1) Georgetown University, N/A, (2) Office of Biostatistics Research, NHLBI, N/A, (3) North Carolina State University, N/A
Co-Author(s):
Amia Graye
Office of Biostatistics Research, NHLBI
First Author:
Presenting Author:
Abstract Text:
Bayesian studies to date involving the Conway-Maxwell-Poisson (COM-Poisson) distribution have little discussion of non- and weakly-informative priors. This work considers various priors and evaluates their influence on the COM-Poisson model via an empirical study under varying dispersion types and sample sizes.
Keywords:
dispersion|over-dispersion|under-dispersion|Bayesian methodology|count data|
Sponsors:
Section on Bayesian Statistical Science
Tracks:
Bayesian Theory and Foundations
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