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ERIC Number: EJ1179425
Record Type: Journal
Publication Date: 2018-Jun
Pages: 12
Abstractor: As Provided
ISSN: ISSN-1098-2140
Bayesian Posterior Odds Ratios: Statistical Tools for Collaborative Evaluations
Hicks, Tyler; Rodríguez-Campos, Liliana; Choi, Jeong Hoon
American Journal of Evaluation, v39 n2 p278-289 Jun 2018
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.
SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail:; Web site:
Publication Type: Journal Articles; Reports - Descriptive
Education Level: N/A
Audience: Researchers
Language: English
Sponsor: Office of Special Education Programs (ED/OSERS)
Authoring Institution: N/A
Grant or Contract Numbers: H326Y120005