In epidemiological studies, participants' disease status is often collected through self-reported outcomes in place of formal medical tests due to budget constraints. However, self-reported outcomes are often subject to measurement errors, and may lead to biased estimates if used in statistical analyses. In this paper, we propose statistical methods to correct for outcome measurement errors in survival analyses with multiple failure types through a reweighting strategy. We also discuss asymptotic properties of the proposed estimators and derive their asymptotic variances. The work is motivated by Conservation of Hearing Study (CHEARS) which aims to evaluate risk factors for hearing loss in the Nurses' Health Studies II (NHS II). We apply the proposed method to adjust for the measurement errors in self-reported hearing outcomes; the analysis results suggest that tinnitus is positively associated with moderate hearing loss at both low or mid and high sound frequencies, while the effects between different frequencies are similar.

翻译：在流行病学研究中，由于预算限制，参与者的疾病状态常通过自我报告结果而非正式医学检测来收集。然而，自我报告结果通常存在测量误差，若用于统计分析可能导致有偏估计。本文提出一种通过重加权策略校正多种失败类型生存分析中结果测量误差的统计方法。我们还讨论了所提估计量的渐近性质，并推导了其渐近方差。本研究的动机源自听力保护研究（CHEARS），该研究旨在评估护士健康研究II（NHS II）中听力损失的风险因素。我们将所提方法应用于校正自我报告听力结果的测量误差；分析结果表明，耳鸣与低中频及高频声音的中度听力损失呈正相关，而不同频率间的效应相似。