怎样绘制结局为四分类的Decision Curve Analysis？请告诉R代码。

您好，以下是R代码实现结局为四分类的Decision Curve Analysis：

library(ggplot2)
library(pROC)
library(CCA)

# 设置初始数据
set.seed(123)
n <- 100
x1 <- rnorm(n, 0, 1)
x2 <- rnorm(n, 1, 1)
x3 <- rnorm(n, 2, 1)
y <- sample(c(0, 1), n, replace = TRUE)
dca_data <- data.frame(X1 = c(x1, x2, x3), X2 = c(x1, x2, x3), Y = y)

# 模型训练
fit_lm <- glm(Y ~ ., data = dca_data, family = binomial)
fit_lrm <- lrm(Y ~ ., data = dca_data)

# 计算概率
p_lm <- predict(fit_lm, type = "response")
p_lrm <- predict(fit_lrm, type = "fitted")

# 绘制DCA曲线
dca_results <- resamples(list(linear = p_lm, logistic = p_lrm),
dca_data$Y, method = "boot", B = 100)
plot(dca_results, schmid = FALSE)

注意：以上代码仅供参考，具体实现还需要根据您的数据和假设进行调整。同时，如果您仍然有疑问，可以参考以下链接：

https://www.r-bloggers.com/2019/08/decision-curve-analysis-with-r/