Understanding the Uncertainty of an Effectiveness-Cost Ratio in Educational Resource Allocation: A Bayesian Approach

Given the necessity to bridge the gap between what happened and what is likely to happen, this paper aims to explore how to apply Bayesian inference to cost-effectiveness analysis so as to capture the uncertainty of a ratio-type efficiency measure. The first part of the paper summarizes the characte...

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Bibliographic Details
Published inSociety for Research on Educational Effectiveness
Main Author Pan, Yilin
Format Report
LanguageEnglish
Published Society for Research on Educational Effectiveness 2016
Subjects
Bayesian Statistics
Comparative Analysis
Computation
Cost Effectiveness
Demonstration Programs
Dropout Prevention
Efficiency
Probability
Resource Allocation
Sampling
Statistical Analysis
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Summary:Given the necessity to bridge the gap between what happened and what is likely to happen, this paper aims to explore how to apply Bayesian inference to cost-effectiveness analysis so as to capture the uncertainty of a ratio-type efficiency measure. The first part of the paper summarizes the characteristics of the evaluation data that are commonly available in educational research, discusses the ratio property and proposes different estimators of interest. The second section synthesizes two perceptions of uncertainty in the literature, and reviews the conventional quantitative methods that address the uncertainty of a ratio under each perception. The third part proposes two Bayesian models that differ in the assumption of site-level variability, and demonstrates the estimation, presentation and interpretation of the results using the comparison of two high school dropout prevention programs: New Chance and JOBSTART. The last section summarizes the strengths and limitations of the Bayesian method, and lists some directions for future exploration. Tables and figures are appended.