Clinical risk prediction models and informative cluster size: Assessing the performance of a suicide risk prediction algorithm

DOI10.1002/BIMJ.202000199zbMath1523.62100MaRDI QIDQ6064186

Susan M. Shortreed, Gregory E. Simon, Unnamed Author, Rebecca Yates Coley, Unnamed Author

Publication date: 12 December 2023

Published in: Biometrical Journal (Search for Journal in Brave)

Full work available at URL: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9134927

zbMATH Keywords

machine learningcorrelated datapredictive analyticsnonignorable cluster sizeelectronic health records

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10)

Cites Work

• Marginal Analyses of Clustered Data When Cluster Size Is Informative
• Bootstrap methods: another look at the jackknife
• Within-cluster resampling
• Informative Cluster Sizes for Subcluster-Level Covariates and Weighted Generalized Estimating Equations
• Estimating the Error Rate of a Prediction Rule: Improvement on Cross-Validation
• Model selection for semiparametric marginal mean regression accounting for within‐cluster subsampling variability and informative cluster size
• An examination of a method for marginal inference when the cluster size is informative
• Methods for observed‐cluster inference when cluster size is informative: A review and clarifications
• Mean estimating equation approach to analysing cluster-correlated data with nonignorable cluster sizes
• Random forests

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