INFERENCES ABOUT EXPOSURE-DISEASE ASSOCIATIONS USING PROBABILITY-OF-EXPOSURE INFORMATION
INFERENCES ABOUT EXPOSURE-DISEASE ASSOCIATIONS USING PROBABILITY-OF-EXPOSURE INFORMATION
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DOI：
10.2307/2290714
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发表时间：
1993-03-01
影响因子：
3.7
通讯作者：
KUPPER, LL
中科院分区：
文献类型：
--
作者：
SATTEN, GA;KUPPER, LL
提出了无条件和条件似然方法，用于对二元疾病变量和仅在概率上已知的暴露变量（例如，通过替代暴露变量的测量）相关的优势和优势比进行建模，同时对协变量向量进行适当调整。假设存在非微分误差，则开发了一种概率结构，该结构允许分析疾病与替代物之间的边际关系，同时保持疾病与真实暴露之间的边际关系的重要属性。特别是，以替代疾病表中的边际总数为条件的分析消除了与真实暴露疾病表的条件分析中消除的相同的干扰参数。此外，还推导了疾病组和无病组的暴露概率（POE）之间的关系，从而允许使用与研究人群结构不同的人群的暴露信息。举例说明了当 POE 值已知或必须使用真实暴露的部分信息来估计时适当的方法；在后一种情况下，暴露数据可以被认为是随机丢失的。
Unconditional and conditional likelihood methods are proposed for modeling odds and odds ratios relating a binary disease variable and an exposure variable that is only known probabilistically (e.g., via measurement of a surrogate exposure variable), while adjusting appropriately for a vector of covariables. Assuming nondifferential errors, a probabilistic structure is developed that permits analysis of the marginal relation between disease and the surrogate while maintaining important properties of the marginal relation between disease and true exposure. In particular, analyses conditioned on marginal totals in surrogate-disease tables remove the same nuisance parameters as are removed in a conditional analysis of true exposure-disease tables. In addition, a relation between the probability of exposure (POE) in the disease and disease-free groups is derived, permitting the use of information about exposure from populations with structure different from the study population. Examples are presented illustrating methods appropriate when the POE values are known or when they must be estimated using partial information on true exposure; in this latter case, the exposure data may be considered to be missing at random.