Probability (p) values are widely used in social science research and evaluation to guide decisions on program and policy changes. However, they have some inherent limitations, sometimes leading to misuse, misinterpretation, or misinformed decisions. Bayesian methods, which use probabilistic inference to determine the importance of a finding, are becoming the primary alternative approach to p-values. But, many researchers lack the knowledge and training to confidently implement a Bayesian analysis. Given the increasing attention to and use of Bayesian methods in social science research, it is essential to understand the underlying assumptions, tradeoffs, validity, and generalizability of results in a Bayesian framework, and the circumstances under which there may be advantages to using it rather than, or in addition to, a frequentist approach. (Author abstract)
Bayesian methods for social policy research and evaluation
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