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stat.ME2023
Flexible cost-penalized Bayesian model selection: developing inclusion paths with an application to diagnosis of heart disease
Erica M. Porter, Christopher T. Franck, Stephen Adams
We propose a Bayesian model selection approach that allows medical practitioners to select among predictor variables while taking their respective costs into account. Medical proce…
stat.ME2023
Boldness-Recalibration for Binary Event Predictions
Adeline P. Guthrie, Christopher T. Franck
Probability predictions are essential to inform decision making across many fields. Ideally, probability predictions are (i) well calibrated, (ii) accurate, and (iii) bold, i.e., s…
stat.ME2019
Detection of latent heteroscedasticity and group-based regression effects in linear models via Bayesian model selection
Thomas A. Metzger, Christopher T. Franck
Standard linear modeling approaches make potentially simplistic assumptions regarding the structure of categorical effects that may obfuscate more complex relationships governing d…