THE DESIGN AND ANALYSIS OF CASE CONTROL STUDIES WITH BIASED SAMPLING
THE DESIGN AND ANALYSIS OF CASE CONTROL STUDIES WITH BIASED SAMPLING
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DOI：
10.2307/2532441
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发表时间：
1990-12-01
期刊：
影响因子：
1.9
通讯作者：
WACHOLDER, S
中科院分区：
文献类型：
--
作者：
WEINBERG, CR;WACHOLDER, S
提出了一种病例对照研究的设计，在该研究中，完全变量确定的受试者的选择共同基于疾病状况和容易获得的可能与疾病相关的“筛查”变量。受试者的招募遵循独立的伯努利抽样方案，招募概率由调查人员事先设定。具体地说，如果与年龄和性别等筛查变量相关的发病率或优势比的预先估计可用，则可以设置抽样以实现平均频率匹配。或者，例如，当研究一种罕见的暴露时，人们可以用特定类别的对象来丰富样本。在这样的设计之后，有两种有效的Logistic回归分析方法，这两种方法都可以有效地估计与筛选变量相关的影响，这些变量被允许对招聘产生偏差。基于渐近性，对大样本和基于模拟的小样本，比较了估计器的统计特性。
A design is proposed for case-control studies in which selection of subjects for full variable ascertainment is based jointly on disease status and on easily obtained "screening" variables that may be related to the disease. Recruitment of subjects follows an independent Bernoulli sampling scheme, with recruitment probabilities set by the investigator in advance. In particular, the sampling can be set up to achieve, on average, frequency matching, provided prior estimates of the disease rates or odds ratios associated with screening variables such as age and sex are available. Alternatively-for example, when studying a rare exposure-one can enrich the sample with certain categories of subject. Following such a design, there are two valid approaches to logistic regression analysis, both of which allow for efficient estimation of effects associated with the screening variables that were allowed to bias the recruitment. The statistical properties of the estimators are compared, both for large samples, based on asymptotics, and for small samples, based on simulations.