  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.
