问题描述
这是我做的图，我想要图的置信区间，上下两部分.到目前为止，我已经生成了上限和下限，但我对包含置信区间的图有问题.
This is a plot I did, I want the confidence intervals for the plot, both upper and lower. I have come so far that I have produced both the upper and lower range but I have problems with the plot that includes the confidence interval.
这是我的几行数据，gdk 是我的二元响应，第二个变量是年龄
Here are a few lines of my data, gdk is my binary response and the second variable is the age
gdk age prog calender
29 FALSE 59 NASTK 11
30 FALSE 59 NASTK 10
91 TRUE 49 NMATK 9
129 TRUE 47 NFYSK 8
227 FALSE 46 LARAA 13
244 TRUE 44 LARAA 11
256 TRUE 41 LARAA 9
311 FALSE 38 NMATK 7
323 FALSE 42 NSFYY 11
393 TRUE 40 LARAA 11
449 FALSE 37 NSFYY 9
450 FALSE 38 NSFYY 10
这是我的第一个情节的代码:
This is the code for my first plot:
prop<-numeric()
for (i in 18:60){prop[i-17]<-mean(both$gdk[both$age==i],na.rm=TRUE)}
mod.red.fin<-glm(respons ~prog+age+calender, family=binomial,data=both)
newdata<-data.frame(prog="NMATK",calender=7, age=18:60)
plot(18:60, predict(mod.red.fin, newdata, type="respons"))
为了增强信心，我使用了以下代码:
to bring up my confidence, I used the code:
newdata<-data.frame(prog="NMATK",calender=7, age=18:60)
newdata2<-cbind(newdata, predict(mod.red.fin, newdata, type="link", se=TRUE))
newdata2<-within(newdata2, {PredictedProb<-plogis(fit)
LL<-plogis(fit-(1.96*se.fit))
UL<-plogis(fit+(1.96*se.fit))})
head(newdata2)
prog calender age fit se.fit residual.scale UL LL PredictedProb
1 NMATK 7 18 1.637162 0.2128354 1 0.8863833 0.7720644 0.8371484
2 NMATK 7 19 1.569661 0.2072370 1 0.8782376 0.7619639 0.8277353
3 NMATK 7 20 1.502160 0.2032196 1 0.8699448 0.7509808 0.8178965
4 NMATK 7 21 1.434660 0.2008779 1 0.8615687 0.7390311 0.8076263
5 NMATK 7 22 1.367159 0.2002708 1 0.8531708 0.7260410 0.7969207
6 NMATK 7 23 1.299658 0.2014139 1 0.8448057 0.7119527 0.7857774
然后我如何绘制置信区间?需要代码方面的帮助.在 library(ggplot2) 上检查了一下，但没有想出任何东西.
how do I then plot the confidence interval? Need help with the code.checked a bit on the library(ggplot2) but did not come up with anything.
推荐答案
如果您想使用 ggplot(可能是创建所需绘图的最简单方法)，请使用 stat_smooth() 几何.
If you want to use ggplot (probably the easiest way to create your desired plots), use the stat_smooth() geom.
但是，您对所需的情节有疑问.使用 ggplot 一次只能绘制 1 个 x 变量.话虽如此，下面是一些示例代码，可以让您说明:
However, you have a problem with your desired plot. You can only have 1 x variable plotted at a time with ggplot. That being said, here's some example code that should get you stated:
d = read.table(header = TRUE, text =
" gdk age prog calender
FALSE 59 NASTK 11
FALSE 59 NASTK 10
TRUE 49 NMATK 9
TRUE 47 NFYSK 8
FALSE 46 LARAA 13
TRUE 44 LARAA 11
TRUE 41 LARAA 9
FALSE 38 NMATK 7
FALSE 42 NSFYY 11
TRUE 40 LARAA 11
FALSE 37 NSFYY 9
FALSE 38 NSFYY 10")
## Convert gkk from T/F to 1/0
d$gdk2 <- as.numeric(d$gdk)
library(ggplot2)
plot1 <- ggplot(data = d, aes(x = age, y = gdk2)) +
stat_smooth(method = 'glm', family = 'binomial') +
theme_bw()
ggsave('plot1.jpg', plot1, width = 6, height = 4)
这给了你这个情节:
plot2
plot2 <- ggplot(data = d, aes(x = calender, y = gdk2)) + stat_smooth(method = 'glm', family = 'binomial') + theme_bw()
ggsave('plot2.jpg', plot2, width = 6, height = 4)
这给了你这个数字.
顺便说一句，我知道 ggplot2 很难学.我建议查看此页面了解更多信息.此外，第一个 Google 对confidence ggplot2"的点击是官方的 ggplot2 文档 用于绘制置信区间.
BTW, I know ggplot2 can be hard to learn. I would suggest checking out this page for more information.Also, the first Google hit for "confidence ggplot2" was the offical ggplot2 documentation for plotting confidence intervals.
这篇关于在 R 中绘制预测概率和置信区间的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！