ArticleJournal of the Royal Statistical Society. Series B, Statistical methodology2023
Monotone response surface of multi-factor condition: estimation and Bayes classifiers.
Article in Journal of the Royal Statistical Society. Series B, Statistical methodology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Multicomponent Behavior Change Technique Intervention for Caregivers of People With Alzheimer Disease and Related Dementias: Protocol for a Single-Arm, Personalized Behavioral Trial to Disrupt Sedentary Time.JMIR research protocols · 2026Article
- EVALUATING MULTIPLEX DIAGNOSTIC TEST USING PARTIALLY ORDERED BAYES CLASSIFIER.The annals of applied statistics · 2026Article
- PRO-ADD: Patient-empowered dose-finding trials integrating safety, preliminary efficacy and patient-reported outcomes for optimal dose selection.Statistical methods in medical research · 2026Article
- Protocol for a single-arm, multi-component behavior change technique (BCT) intervention to develop a walking habit among caregivers for persons with Alzheimer disease and related dementias (ADRD).Contemporary clinical trials · 2026Article
- A Novel Method for Inserting Dose Levels Mid-Trial in Early-Phase Oncology Combination Studies.Statistics in medicine · 2026Article
- Breaking up prolonged sedentary behavior to improve cardiometabolic health (BREAK2): protocol for a dose-finding adaptive randomization trial.BMC public health · 2025Article
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2 authors.
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Abstract
We formulate the estimation of monotone response surface of multiple factors as the inverse of an iteration of partially ordered classifier ensembles. Each ensemble (called PIPE-classifiers) is a projection of Bayes classifiers on the constrained space. We prove the inverse of PIPE-classifiers (iPIPE) exists, and propose algorithms to efficiently compute iPIPE by reducing the space over which optimisation is conducted. The methods are applied in analysis and simulation settings where the surface dimension is higher than what the isotonic regression literature typically considers. Simulation shows iPIPE-based credible intervals achieve nominal coverage probability and are more precise compared to unconstrained estimation.
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