使用confint()估计GLMM的CI时出错 [英] Error when estimating CI for GLMM using confint()

问题描述

我有一组GLMM，它们装有二进制响应变量和一组连续变量，并且我想获得每个模型的置信区间.我一直在使用95％的 confint()函数，并使用 profile 方法，如果将其应用于没有交互作用的模型，它将可以正常工作.

I have a set of GLMMs fitted with a binary response variable and a set of continuous variables, and I would like to get confidence intervals for each model. I've been using confint() function, at 95% and with the profile method, and it works without any problems if it is applied to a model with no interactions.

但是，当我将 confint()应用于具有交互作用(连续*连续)的模型时，我得到了这个错误:

However, when I apply confint() to a model with interactions (continuous*continuous), I've been getting this error:

m1CI <- confint(m1, level=0.95, method="profile")

zeta中的错误(shiftpar，开始= opt [seqpar1] [-w]):分析发现新的，较低的偏差

Error in zeta(shiftpar, start = opt[seqpar1][-w]) : profiling detected new, lower deviance

模型运行没有问题(尽管我应用了优化器，因为某些模型存在收敛问题)，这是其中一个的最终形式:

The model runs without any problem (although I applied an optimizer because some of the models were having problems with convergence), and here is the final form of one of them:

m1 <- glmer(Use~RSr2*W+RSr3*W+RShw*W+RScon*W+
 RSmix*W+(1|Pack/Year),
 control=glmerControl(optimizer="bobyqa", 
    optCtrl=list(maxfun=100000)), 
   data = data0516RS, family=binomial(link="logit"))

有人知道为什么会这样吗，我该如何解决呢?

Does anyone know why this is happening, and how can I solve it?

我正在使用R版本3.4.3和lme4 1.1-17

I am using R version 3.4.3 and lme4 1.1-17

推荐答案

此问题已通过以下说明解决:

The problem was solved by following these instructions:

该错误消息表示在分析过程中，优化程序发现了拟合值要好得多(以'devtol'参数)比假定的最小偏差解决方案返回首先.您可以提升'devtol'参数(即当前设置为保守的1e-9 ...)，如果您想忽略这一点-但是，非单调的配置文件也警告您可能对个人资料不了解.

The error message indicates that during profiling, the optimizer found a fitted value that was significantly better (as characterized by the 'devtol' parameter) than the supposed minimum-deviance solution returned in the first place. You can boost the 'devtol' parameter (which is currently set at a conservative 1e-9 ...) if you want to ignore this -- however, the non-monotonic profiles are also warning you that something may be wonky with the profile.

来自 https://stat.ethz.ch/pipermail/r-sig-mixed-models/2014q3/022394.html

我使用了 lme4 包中的 confint.merMod ，并将'devtol'参数提升为1e-8，这对我的模型不起作用，然后转到1e-7.有了这个值，它就起作用了

I used the confint.merModfrom the lme4 package, and boosted the 'devtol' parameter, first to 1e-8, which didn't work for my models, and then to 1e-7. With this value, it worked

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