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Valid and efficient imprecise-probabilistic inference with partial priors, II. General framework
Ryan Martin
Bayesian inference requires specification of a single, precise prior distribution, whereas frequentist inference only accommodates a vacuous prior. Since virtually every real-world…
Generalized Bayes inference on a linear personalized minimum clinically important difference
Pei-Shien Wu, Ryan Martin
Inference on the minimum clinically important difference, or MCID, is an important practical problem in medicine. The basic idea is that a treatment being statistically significant…
Turning the information-sharing dial: efficient inference from different data sources
Emily C. Hector, Ryan Martin
A fundamental aspect of statistics is the integration of data from different sources. Classically, Fisher and others were focused on how to integrate homogeneous (or only mildly he…
Valid and efficient imprecise-probabilistic inference with partial priors, I. First results
Ryan Martin
Between Bayesian and frequentist inference, it's commonly believed that the former is for cases where one has a prior and the latter is for cases where one has no prior. But the pr…