el Lozy M
J Chronic Dis. 1983;36(3):237-49. doi: 10.1016/0021-9681(83)90058-9.
Dietary intakes are subject to measurement errors and to day-to-day variation, which have contributed to obscuring the suspected relation between dietary lipids and ischemic heart disease. The effect of measurement error on the correlation between dietary intakes and serum cholesterol levels has been studied by others. In this paper we study the effects of errors on the categorization of subjects according to the quantities of their intakes, and the effects of this misclassification on the observed relation between observed dietary intakes and disease. Our model is based on a bivariate normal joint distribution of true and observed intakes, from which various conditional probabilities can be calculated. Tables are given to simplify many of these computations. We conclude that the usual period of collection of dietary records, 1 week, is usually adequate. The model developed is applicable to any measurement recorded with error, and two examples of its application to the classification of subjects as normotensive or hypertensive are given. The model does depend on a large number of assumptions, some of which are clearly not met. Hence the actual numerical values obtained should be treated with some scepticism. If, however, the assumptions are approximately met, then the results should be reasonable approximations to the truth.
饮食摄入量存在测量误差和每日波动，这使得饮食脂质与缺血性心脏病之间的疑似关系变得模糊。其他人已经研究了测量误差对饮食摄入量与血清胆固醇水平之间相关性的影响。在本文中，我们研究了误差对根据摄入量对受试者进行分类的影响，以及这种错误分类对观察到的饮食摄入量与疾病之间关系的影响。我们的模型基于真实摄入量和观察到的摄入量的二元正态联合分布，由此可以计算各种条件概率。给出了表格以简化许多此类计算。我们得出结论，通常收集饮食记录的1周时间通常就足够了。所开发的模型适用于任何存在误差记录的测量，并且给出了其应用于将受试者分类为血压正常或高血压的两个示例。该模型确实依赖于大量假设，其中一些显然不成立。因此，所获得的实际数值应持一定的怀疑态度。然而，如果假设大致成立，那么结果应该是对真实情况的合理近似。
