纵向肺功能数据测量误差的计算机模拟

Robert E. Dales , James A. Hanley, Pierre Ernst, Margaret R. Becklake
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引用次数: 9

摘要

在两项涉及纵向肺功能数据的流行病学研究设计中,测量误差对结果准确性的影响使用计算机建模进行了评估。创建了五个实际数据集(队列),每组400名受试者,其中一半暴露于其影响程度接近吸烟的物质。在每个队列中,经过6年、4年和2年的观察,在FEV1水平的测量中有无误差,对FEV1下降进行建模。对于每个观察时间,使用随访设计比较暴露组之间的FEV1下降,并使用病例对照设计比较FEV1下降前20百分位受试者(病例)的暴露风险与暴露后20百分位受试者(对照组)的暴露风险,来估计暴露对下降的影响。在两项研究设计中,只有在6年的观察后才能持续检测到p0.01的暴露效应。
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Computer modelling of measurement error in longitudinal lung function data

The effect of measurement error on the accuracy of results in two epidemiological study designs involving longitudinal lung function data was assessed using computer modelling. Five realistic data sets (cohorts) were created, each of 400 subjects, half of whom were exposed to an agent whose effects approximated in magnitude that of cigarette smoking. In each cohort, FEV1 decline was modelled after 6, 4 and 2 years of observation with and without error in the measurement of level of FEV1. For each length of observation the effect of exposure on decline was estimated using a follow-up design comparing the FEV1 decline between exposure groups, and a case-control design comparing risk of exposure in subjects in the top 20th percentile of FEV1 decline (cases) to exposure in those in the bottom 20th percentile (controls). For both study designs an exposure effect at p 0.01 could only be consistently detected after 6 years of observation.

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