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Bayesian estimates from experimental data can be influenced by highly diffuse or “uninformative” priors. This paper gives examples of how diffuse priors can affect estimates, and discusses how practitioners can use their expertise to critique and select a prior. 1
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James R. Bland (2025) studied this question.
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