Evaluating risk-prediction models using data from electronic health records

DOI10.1214/15-AOAS891zbMath1358.62109WikidataQ31093599 ScholiaQ31093599MaRDI QIDQ288590

Le Wang, Benjamin French, Hansie M. Mathelier, Pamela A. Shaw, Stephen E. Kimmel

Publication date: 27 May 2016

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.aoas/1458909917

zbMATH Keywords

prediction accuracyROC curvesoutcome misclassificationrisk reclassificationrobustness of prediction accuracy

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Robustness and adaptive procedures (parametric inference) (62F35)

Related Items (2)

Evaluating risk-prediction models using data from electronic health records ⋮ Improved generalized raking estimators to address dependent covariate and failure‐time outcome error

Uses Software

• bootstrap
• BLINPLUS
• relibpls8

Cites Work

• Unnamed Item
• Evaluating risk-prediction models using data from electronic health records
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• Inference using surrogate outcome data and a validation sample
• The Effects of Misclassification on the Estimation of Relative Risk
• A Detailed Evaluation of Adjustment Methods for Multiplicative Measurement Error in Linear Regression with Applications in Occupational Epidemiology
• Time‐Dependent ROC Curves for Censored Survival Data and a Diagnostic Marker
• A mean score method for missing and auxiliary covariate data in regression models
• Bias and efficiency loss due to misclassified responses in binary regression
• Performance of reclassification statistics in comparing risk prediction models
• Survival Model Predictive Accuracy and ROC Curves

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