Methods for estimating the optimal number and location of cut points in multivariate survival analysis: a statistical solution to the controversial effect of BMI

DOI10.1007/S00180-019-00908-9zbMath1505.62092OpenAlexW2953494463WikidataQ127620248 ScholiaQ127620248MaRDI QIDQ2282593

Meng-Ke Hsieh, Yi-Hsuan Tsai, An Jen Chiang, Chung Chang, Jiabin Chen, Chia-Chiung Liu

Publication date: 8 January 2020

Published in: Computational Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00180-019-00908-9

zbMATH Keywords

Monte Carlo methodcross-validationAICcut points

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08)

Related Items (1)

Binacox: automatic cut‐point detection in high‐dimensional Cox model with applications in genetics

Uses Software

• rgenoud
• Unnamed Item

Cites Work

• Unnamed Item
• Unnamed Item
• Survival analysis. Techniques for censored and truncated data
• Maximally Selected Chi Square Statistics
• Flexible hazard ratio curves for continuous predictors in multi-state models
• Introduction to evolutionary computing

This page was built for publication: Methods for estimating the optimal number and location of cut points in multivariate survival analysis: a statistical solution to the controversial effect of BMI