Distribution-free predictive inference in health sciences: a review of conformal prediction methods for biostatistics and epidemiology

Biostatistics and Epidemiology · Available online 23 Jul 2026 · In press · DOI 10.1080/24709360.2026.2685947

Authors (6)

Ce Zhang, Hongni Wang, Lingzhu Li, Bei Jiang, Xiaodong Yan, Linglong Kong

Abstract

PubPorta does not have an abstract for this article yet.

Read the article at the publisher →

Publication details

Year

2026

Citation

Zhang, C., Wang, H., Li, L., et al. (2026). Distribution-free predictive inference in health sciences: a review of conformal prediction methods for biostatistics and epidemiology. Biostatistics and Epidemiology. https://doi.org/10.1080/24709360.2026.2685947

Related articles

• Unlocking better bladder cancer care with AMAZON: adaptive quantile monitoring under progressive censoring · Biostatistics and Epidemiology · 2026 · Same journal
• Modeling time taken to HIV testing and uptake of test results: extension of the PWP model to handle time-dependent covariates · Biostatistics and Epidemiology · 2023 · Same journal
• Modeling time to event for epicenters of the pandemic COVID-19 · Biostatistics and Epidemiology · 2023 · Same journal
• Modeling incubation period and time of exposure using the four-parameter generalized gamma distribution · Biostatistics and Epidemiology · 2026 · Same journal
• Finite Markov chains with absorbing states and mis-specified random effects: application to cognitive data · Biostatistics and Epidemiology · 2025 · Same journal
• Public transportation network scan for rapid surveillance · Biostatistics and Epidemiology · 2022 · Same journal
• Doubly weighted estimating equations and weighted multiple imputation for causal inference with an incomplete subgroup variable · Biostatistics and Epidemiology · 2022 · Same journal
• Bayesian multinomial model with inference based on Pólya-Gamma augmentation · Biostatistics and Epidemiology · 2024 · Same journal
• Public transportation network scan for rapid surveillance · Biostatistics and Epidemiology · 2022 · Same journal
• A comparative analysis of time series models for forecasting recovered and deceased COVID-19 cases in India · Biostatistics and Epidemiology · 2026 · Same journal