Risk functions with outcome measurement error
Jessie K Edwards et al.
Abstract
Mortality risk estimated from studies that ascertain date of death through linkage to vital statistics registries may be subject to outcome measurement error. As a result, some deaths among study participants may not be captured, some study participants who are alive may be falsely categorized as deceased, and some deaths may be recorded at incorrect times, leading to bias in estimates of mortality risk and survival. Here, we illustrate an extension of the Rogan-Gladen estimator to account for outcome measurement error in risk and survival functions in settings with right censoring. As a motivating application, we consider and account for outcome measurement error that could be induced by incomplete and/or incorrect linkage to death registries when estimating mortality risk among people entering care for HIV in the University of North Carolina Center for AIDS Research HIV Clinical Cohort between 2001 and 2022. A series of simulation studies demonstrates that the approach performed well even when participants selected into the validation study were at higher mortality risk than the main study. The proposed approach may be parameterized using internal or external validation data or used as a form of quantitative bias analysis.
1 citation
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.16 × 0.4 = 0.06 |
| M · momentum | 0.53 × 0.15 = 0.08 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.