%0 Journal Article
%T Bayesian Posterior Odds Ratios:  Statistical Tools for Collaborative Evaluations
%A Jeong Hoon Choi
%A Liliana Rodr¨ªguez-Campos
%A Tyler Hicks
%J American Journal of Evaluation
%@ 1557-0878
%D 2018
%R 10.1177/1098214017704302
%X To begin statistical analysis, Bayesians quantify their confidence in modeling hypotheses with priors. A prior describes the probability of a certain modeling hypothesis apart from the data. Bayesians should be able to defend their choice of prior to a skeptical audience. Collaboration between evaluators and stakeholders could make their choices more defensible. This article describes how evaluators and stakeholders could combine their expertise to select rigorous priors for analysis. The article first introduces Bayesian testing, then situates it within a collaborative framework, and finally illustrates the method with a real example
%K Bayesian statistics
%K collaborative evaluation
%K Bayes¡¯s factor
%K posterior odds ratios
%U https://journals.sagepub.com/doi/full/10.1177/1098214017704302