Interpreting parameters in the logistic regression model with random effects
Interpreting parameters in the logistic regression model with random effects
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DOI：
10.1111/j.0006-341x.2000.00909.x
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发表时间：
2000-09-01
期刊：
影响因子：
1.9
通讯作者：
Endahl, L
中科院分区：
文献类型：
--
作者：
Larsen, K;Petersen, JH;Endahl, L
在具有非独立结果的情况下，采用随机效应Logistic回归来研究解释变量与二元结果之间的关系。在本文中，我们详细研究了固定效应和随机效应参数的解释。作为异质性度量，模型中包含的随机效应参数不容易解释。我们讨论了异质性的不同替代措施，并建议使用中位数优势比措施，这是原始随机效应参数的函数。这种方法可以用众所周知的比值比进行简单的解释，这极大地促进了数据分析师和主题研究人员之间的沟通。来自不同学科领域的三个例子，主要来自我们自己的经验，用于激励和说明这些模型中参数解释的不同方面。
Logistic regression with random effects is used to study the relationship between explanatory variables and a binary outcome in cases with nonindependent outcomes. In this paper, we examine in detail the interpretation of both fixed effects and random effects parameters. As heterogeneity measures, the random effects parameters included in the model are not easily interpreted. We discuss different alternative measures of heterogeneity and suggest using a median odds ratio measure that is a function of the original random effects parameters. The measure allows a simple interpretation, in terms of well-known odds ratios, that greatly facilitates communication between the data analyst and the subject-matter researcher. Three examples from different subject areas, mainly taken from our own experience, serve to motivate and illustrate different aspects of parameter interpretation in these models.