画logistic_【R语言】logistic回归+nomogram绘制+c-index+校正曲线
时间: 2023-12-08 14:06:22 浏览: 60
好的,以下是R语言中绘制logistic回归的代码以及nomogram、c-index和校正曲线绘制的示例代码:
首先,我们需要准备一个数据集,这里我们使用R自带的乳腺癌数据集:
```R
data("breast_cancer", package = "rpart")
# 将目标变量转换为二分类变量
breast_cancer$Class[breast_cancer$Class == "negative"] <- 0
breast_cancer$Class[breast_cancer$Class == "positive"] <- 1
```
接下来,我们使用glm函数来拟合一个logistic回归模型:
```R
model <- glm(Class ~ Age + Menopause + Tumor.Size + Inv.Nodes,
data = breast_cancer, family = binomial(link = "logit"))
```
接下来,我们可以使用rms包中的nomogram函数来绘制一个nomogram:
```R
library(rms)
# 绘制nomogram
nom <- nomogram(model, fun = function(x) 1/(1+exp(-x)))
print(nom)
```
然后,我们可以使用rms包中的validate函数来计算c-index和绘制校正曲线:
```R
# 计算c-index
valid <- validate(model, B = 100)
valid$c.index
# 绘制校正曲线
plot(valid$cal, ylim = c(0, 1), xlab = "Predicted Probabilities", ylab = "Observed Probabilities")
```
最后,我们可以使用ggplot2包中的ggplot函数来绘制logistic回归的曲线:
```R
library(ggplot2)
# 计算预测概率
breast_cancer$pred_prob <- predict(model, type = "response")
# 绘制曲线
ggplot(breast_cancer, aes(x = Age, y = pred_prob, color = Class)) +
geom_smooth(method = "glm", method.args = list(family = "binomial"), se = FALSE) +
scale_color_manual(values = c("#999999", "#E69F00")) +
labs(title = "Logistic Regression Curve", x = "Age", y = "Predicted Probability",
color = "Class", subtitle = "Breast Cancer Data") +
theme_bw()
```
希望这些代码能对你有所帮助!