Kupper L L
Am J Epidemiol. 1984 Oct;120(4):643-8. doi: 10.1093/oxfordjournals.aje.a113926.
When certain key factors of interest in epidemiologic research studies cannot be measured directly, epidemiologists often turn to the use of surrogate variables. The potential bias in making statistical inferences about an adjusted exposure-disease association parameter (e.g., a partial correlation) is described as a function of the degree of unreliability in the surrogate variables used in place of the underlying disease, exposure, and confounding factors of real interest. It is shown that unreliability in the surrogate confounder is much more apt to produce seriously misleading inferences than is unreliability in the surrogate measures for disease and exposure. Practical methods are discussed for dealing with less than perfectly reliable surrogate variables.
当流行病学研究中某些关键的感兴趣因素无法直接测量时，流行病学家常常会转而使用替代变量。关于调整后的暴露-疾病关联参数（例如偏相关）进行统计推断时的潜在偏差，被描述为是所使用的替代潜在疾病、暴露及真正感兴趣的混杂因素的变量不可靠程度的函数。结果表明，替代混杂因素的不可靠性比疾病和暴露的替代测量的不可靠性更易于产生严重误导性的推断。文中讨论了处理可靠性欠佳的替代变量的实用方法。
