Landin R, Freedman L S, Carroll R J
Marion Merrell Dow Inc., Kansas City, Missouri 64137, USA.
Biometrics. 1995 Mar;51(1):169-81.
In measuring food intake, three common methods are used: 24-hour recalls, food frequency questionnaires and food records. Food records or 24-hour recalls are often thought to be the most reliable, but they are difficult and expensive to obtain. The question of interest to us is to use the food records or 24-hour recalls to examine possible systematic biases in questionnaires as a measure of usual food intake. In Freedman, et al. (1991), this problem is addressed through a linear errors in variables analysis. Their model assumes that all measurements on a given individual have the same mean and variance. However, such assumptions may be violated in at least two circumstances, as in for example the Women's Health Trial Vanguard Study and in the Finnish Smokers' Study. First, some studies occur over a period of years, and diets may change over the course of the study. Second, measurements might be taken at different times of the year, and it is known that diets differ on the basis of seasonal factors. In this paper, we will suggest new models incorporating mean and variance offsets, i.e., changes in the population mean and variance for observations taken at different time points. The parameters in the model are estimated by simple methods, and the theory of unbiased estimating equations (M-estimates) is used to derive asymptotic covariance matrix estimates. The methods are illustrated with data from the Women's Health Trial Vanguard Study.
在测量食物摄入量时，常用三种方法：24小时回顾法、食物频率问卷法和食物记录法。食物记录法或24小时回顾法通常被认为是最可靠的，但获取这些信息既困难又昂贵。我们感兴趣的问题是，使用食物记录法或24小时回顾法来检验问卷中可能存在的系统偏差，以此作为通常食物摄入量的一种衡量方法。在弗里德曼等人（1991年）的研究中，这个问题通过变量线性误差分析得以解决。他们的模型假定，对给定个体的所有测量值具有相同的均值和方差。然而，至少在两种情况下，这样的假设可能会被违背，例如在妇女健康试验先锋研究和芬兰吸烟者研究中。首先，一些研究持续数年，在此期间饮食可能会发生变化。其次，测量可能在一年中的不同时间进行，而且众所周知，饮食会因季节因素而有所不同。在本文中，我们将提出包含均值和方差偏移的新模型，即针对在不同时间点进行的观测，总体均值和方差的变化。模型中的参数通过简单方法进行估计，并使用无偏估计方程（M估计）理论来推导渐近协方差矩阵估计值。文中用妇女健康试验先锋研究的数据对这些方法进行了说明。
