Predictively consistent priors let complex Bayesian models match or beat the out-of-sample performance of selected simpler models across linear, logistic, and nonlinear examples without explicit selection.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
BART analysis of PATH Waves 3-4 finds e-cigarette use has a null effect on smoking days among never-smoking adolescents and a diversionary effect among ever-smokers, eliminating the gateway effect reported by prior logistic regression models.
citing papers explorer
-
To select or not to select: predictively consistent priors instead of model selection
Predictively consistent priors let complex Bayesian models match or beat the out-of-sample performance of selected simpler models across linear, logistic, and nonlinear examples without explicit selection.
-
Logistic regression is not enough: The need for Bayesian nonparametric modelling for causal inference using observational data, exemplified by the 'gateway' effect
BART analysis of PATH Waves 3-4 finds e-cigarette use has a null effect on smoking days among never-smoking adolescents and a diversionary effect among ever-smokers, eliminating the gateway effect reported by prior logistic regression models.