带有库“效果"的GLMM图中的缩放轴被缩放. [英] Scaling axis in a GLMM plot with library "effects"

问题描述

我是一名生物学专业的毕业生，试图使用R和库"effects"绘制我的GLMM.

I'm a biology graduate trying to plot my GLMM using R and the library "effects".

我正在尝试使用此字符串绘制模型，并且效果很好.

I'm trying to plot my model using this string, and it works perfectly.

library(effects) 
mod.cowles <- glmer((preshunt)~road+(1|area),family=binomial)
eff.cowles <- allEffects(mod.cowles) 
plot(eff.cowles, main= FALSE,rug=FALSE,colors=1, band.colors=3, col=1)

我的问题是我需要从0到0.5的值以及相同的缩放比例的相同轴心的轴.我正在尝试通过将其添加到脚本中来实现这一目标

My problem is that I need the axis with the same lims, starting from 0 to 0.5 values and with the same scaling. I'm trying to do that by adding them to the script

mod.cowles <- glmer((preshunt)~road+(1|area),family=binomial)
eff.cowles <- allEffects(mod.cowles) 
plot(eff.cowles, main= FALSE,rug=FALSE,colors=1, band.colors=3, col=1, xlim=c(0,0.5), ylim=c(0,0.5))

但是随后R只是决定给我一个空图，甚至没有正确的轴.

But then R just decides to give me an empty graph, not even with the correct axis.

有人可以给我提示如何解决这个问题吗?

Can anybody give me a hint on how to solve this problem?

推荐答案

我写信给函数John Fox的作者，得到一个答复，y上的值实际上是对数刻度(:facepalm :，这是逻辑回归！).将原始"值转换为logit并返回是相当简单的.

I wrote to the author of the function John Fox and got a reply that the values on y are actually on logit scale (:facepalm:, it's a logistic regression!). It's fairly trivial to convert "raw" values to logit and back.

这是一个可复制的示例:

Here's a reproducible example:

library(effects) 
library(lme4)

mod.cowles <- glmer(volunteer ~ extraversion + (1|sex), 
                    family=binomial, data = Cowles) # doesn't converge
eff.cowles <- allEffects(mod.cowles) 

plot(eff.cowles, main= FALSE,rug=FALSE,colors=1, band.colors=3, col=1, 
     xlim=c(0, 20), ylim = qlogis(c(0.1, 0.6))) # also log(c(.1, .6)/c(.6, .1))

您可以设置 ylim = qlogis(c(0.01，0.99))，您将获得以下图表.请注意，这是对数刻度，其中0和1是(-)Inf .

You can set ylim = qlogis(c(0.01, 0.99)) and you'll get the below plot. Mind that this is on logit scale where 0 and 1 are (-)Inf.

qlogis(seq(0, 1, by = 0.1))
[1] -Inf -2.1972246 -1.3862944 -0.8472979 -0.4054651 0.0000000
    0.4054651 0.8472979 1.3862944 2.1972246 Inf

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