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首页> 外文期刊>Annals of epidemiology >A method for imputing missing data in longitudinal studies.
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A method for imputing missing data in longitudinal studies.

机译:一种在纵向研究中估算缺失数据的方法。

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PURPOSE: In a cohort in which racial data are unknown for some persons, race-specific persons and person-years are imputed using a model-based iterative allocation algorithm (IAA). METHODS: An EM algorithm-based approach to address misclassification in a censored data regression setting can be adapted to estimate the probability that a person of unknown race is white. The corresponding race-specific person-years are obtained as a by-product of the estimation procedure. Variance estimates are computed using the bootstrap. The proposed approach is compared with the proportional allocation method (PAM). RESULTS: In an occupational cohort where racial data were missing for 41% of the workers, the age-time-race-specific person-years were estimated within a relative variation of approximately 20%, using the IAA. The deaths were less reliably estimated. The standardized mortality ratios (SMRs) for all-cause mortality estimated using the IAA and the PAM were more similar for the non-white workers than for a smaller subgroup of white workers. CONCLUSIONS: The IAA provides a method to reliably estimate race-specific person-year denominators in cohort studies with missing racial data. This method is applicable to other incompletely observed non-time-dependent categorical covariates. Internal cohort rates or SMRs can be computed and modeled, with bootstrap confidence intervals that account for the uncertainty in the determination of race.
机译:目的:在某些人的种族数据未知的队列中,使用基于模型的迭代分配算法(IAA)估算特定种族的人和人年。方法:一种基于EM算法的方法可以解决审查数据回归设置中的错误分类问题,从而可以估算未知种族的人是白人的概率。相应的特定种族的人年作为估算程序的副产品获得。使用引导程序计算方差估计。将该方法与比例分配方法(PAM)进行了比较。结果:在一个职业队列中,有41%的工人缺少种族数据,使用IAA估算出特定于年龄,种族和种族的人年相对偏差在20%左右。死亡人数的估计不够可靠。使用IAA和PAM估算的全因死亡率的标准化死亡率比(SMR)与非白人工人相比要小得多。结论:IAA提供了一种在缺少种族数据的队列研究中可靠地估计特定种族的人年分母的方法。此方法适用于其他未完全观察到的非时间依赖性分类协变量。内部队列率或SMR可以通过自举置信区间进行计算和建模,该区间说明了种族确定的不确定性。

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