在多级logistic回归中，SE怎么能高于1000? [英] How can a SE be above 1000 in a multilevel logistic regression?

问题描述

也许我的问题将无法具体说明，但是在拟合glme模型(在R中使用lme4软件包)时，我得到了参数SE = 1000之一，估计参数高达16.该变量是二分变量.我的问题是，考虑到其他参数的参数和SE似乎还可以，

Maybe my question will fail to be specific but when fitting a glme model (using lme4 package in R) I get for one of the parameters SE=1000, with the estimated parameter as high as 16. The variable is a dichotomous variable. My question is if there might be an explanation for such a result, considering that the other parameters have parameters and SE that seem ok

推荐答案

这表明您已经完全分开.您应该在没有该协变量的情况下重新运行模型.由于它是一个ME模型，因此您可能需要按级别协变量对结果进行制表，以查看正在发生的情况.更多详细信息将使我们的回答更具针对性.

That's a sign that you have complete separation. You should re-run the model without that covariate. Since its an ME model you may need to do a tabulation of outcome by covariate by levels to see what is happening. More details would allow greater specificity in our answers.

这是指向Jarrod Hadfield的帖子的链接， R混合模型邮件列表中的guRus之一.它演示了完全分离是如何导致Hauck-Donner效应的，并提供了一些进一步的方法来尝试对其进行处理.

This is a link to a posting by Jarrod Hadfield, one of the guRus on the R mixed model mailing list. It demonstrates how complete separation leads to the Hauck-Donner effect, and it offers some further approaches to attempt dealing with it.

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