如何在stat_poly_eq的geom_smooth相关图中添加95%置信区间标签

我在绘制数据相关图时，需要在标签中同时报告R²值和相关系数的95%置信区间（CI），尝试在stat_poly_eq的label参数中添加after_stat(conf.int.label)，但出现错误提示找不到该对象。

我的代码如下：

Kan.PS_moc_plot <- Fnlcor_df %>%
  ggplot(aes(x= PSKannada, y= MOC))+
  geom_smooth(method = "lm", se = TRUE, alpha = 0.5)+
  geom_point(size = 2)+
  stat_poly_eq(method = "lm",
               aes(label= paste(after_stat(rr.label), after_stat(p.value.label), after_stat(conf.int.label), sep = "*\",\"*")), 
               label.x = "right", label.y = "bottom",
               size=4, family = "Palatino") + 
  labs(y=" MOC Median RT diffecrence (sec)", x="Kannada Phoneme Segmenation")+  
  facet_wrap(.~paste("Age Range:", AgeRange) + paste("Group:", Group)) + 
  theme_classic() 

Kan.PS_moc_plot

运行后出现以下错误：

`geom_smooth()` using formula = 'y ~ x' Error in `stat_poly_eq()`: ! Problem while mapping stat to aesthetics. ℹ Error occurred in the 3rd layer. Caused by error in `after_stat()`: ! object 'conf.int.label' not found Run `rlang::last_trace()` to see where the error occurred.

stat_poly_eq本身并未内置conf.int.label这个统计量，要实现需求，需要手动分组计算所需统计量，再添加到图中，步骤如下：

1. 分组计算R²和置信区间
   借助broom包拟合线性模型，按AgeRange和Group分组提取R²值以及相关系数的95%置信区间：

   library(broom)
   library(dplyr)
   
   # 分组计算统计指标
   stats_df <- Fnlcor_df %>%
     group_by(AgeRange, Group) %>%
     do({
       model <- lm(MOC ~ PSKannada, data = .)
       tidy_model <- tidy(model, conf.int = TRUE) %>% filter(term == "PSKannada")
       r_sq <- summary(model)$r.squared
       tibble(
         r_squared = r_sq,
         conf_low = tidy_model$conf.low,
         conf_high = tidy_model$conf.high
       )
     }) %>%
     ungroup() %>%
     mutate(
       r_sq_label = sprintf("R² = %.3f", r_squared),
       ci_label = sprintf("95%% CI: [%.3f, %.3f]", conf_low, conf_high)
     )
   

2. 修改绘图代码，添加自定义标签
   使用geom_text()将计算好的标签添加到图中，定位在右下角（和原代码的label.x = "right", label.y = "bottom"一致）：

   Kan.PS_moc_plot <- Fnlcor_df %>%
     ggplot(aes(x = PSKannada, y = MOC)) +
     geom_smooth(method = "lm", se = TRUE, alpha = 0.5) +
     geom_point(size = 2) +
     # 添加自定义统计标签
     geom_text(
       data = stats_df,
       aes(x = Inf, y = -Inf, label = paste(r_sq_label, ci_label, sep = "\n")),
       hjust = 1, vjust = 0, size = 4, family = "Palatino"
     ) +
     labs(
       y = "MOC Median RT difference (sec)", 
       x = "Kannada Phoneme Segmentation"
     ) +
     facet_wrap(.~paste("Age Range:", AgeRange) + paste("Group:", Group)) +
     theme_classic()
   
   Kan.PS_moc_plot
   

内容的提问来源于stack exchange，提问作者Arpitha