Semiparametric time to event models in the presence of error-prone, self-reported outcomes -- with application to the women's health initiative

DOI10.1214/15-AOAS810zbMath1397.62452arXiv1509.04080OpenAlexW1935899947WikidataQ35911630 ScholiaQ35911630MaRDI QIDQ746661

Yunsheng Ma, Xiangdong Gu, Raji Balasubramanian

Publication date: 28 October 2015

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

Full work available at URL: https://arxiv.org/abs/1509.04080

zbMATH Keywords

interval censoringpanel datameasurement errortime to event outcomes

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Estimation in survival analysis and censored data (62N02)

Related Items (6)

Repeated responses in misclassification binary regression: A Bayesian approach ⋮ Semiparametric time to event models in the presence of error-prone, self-reported outcomes -- with application to the women's health initiative ⋮ Regression analysis of misclassified current status data ⋮ icensmis ⋮ A Modified Random Survival Forests Algorithm for High Dimensional Predictors and Self-Reported Outcomes ⋮ Interval-censored data with misclassification: a Bayesian approach

Uses Software

• R
• CRAN

Cites Work

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• A Proportional Hazards Model for Interval-Censored Failure Time Data
• Bias and efficiency loss due to misclassified responses in binary regression

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