重复测量图：叠加平均轨迹和误差线 (ggplot2)

Posted 2023-02-16

【中文标题】重复测量图：叠加平均轨迹和误差线 (ggplot2)

【英文标题】：Repeated measures plot: overlay mean trajectory and error bars (ggplot2)

【发布时间】：2021-11-10 13:42:27

【问题描述】：

我制作了两张重复测量分数的图。第一个图是个人分数（即，绘制了每个参与者的分数）。第二个是平均分数和误差线图。我想组合这两个图，以便第二个图覆盖第一个图，或者将平均轨迹和误差条添加到第一个图。如何做到这一点？

示例数据和创建图的代码如下。

代码

# Renames variables for reshaping  
names(data_wide) [names(data_wide) == "score.baseline"] <- "score.0"
names(data_wide) [names(data_wide) == "score.wave1"] <- "score.1"
names(data_wide) [names(data_wide) == "score.wave2"] <- "score.2"
names(data_wide) [names(data_wide) == "score.wave3"] <- "score.3"

#Convert wide-formatted data into long  
data_long <- reshape(as.data.frame(data_wide), 
                             idvar="ID", 
                             varying=c("score.0", "score.1", "score.2", "score.3"),
                             direction="long")

# Prepare means data

data_long.group <- data_long %>% 
                    group_by(time) %>% 
                    summarise(
                    score_mean = (mean(score, na.rm=TRUE)),
                    score_sd = (sd(score, na.rm=TRUE))
                    ) 

# Plot individual scores

ggplot(data_long, aes(x = factor(time), y = score, color = as.factor(ID), group = ID)) + 
  geom_line(size=0.2) + 
  theme_classic(base_size = 18) + 
  theme(legend.position = "none") + 
  labs(title = "Trajectories", y = "data score", x = "Wave") 

# Plot group-level means and SDs 

ggplot(data_long.group, aes(x = time, y = score_mean)) + 
  geom_line(size=0.2) + 
  theme_classic(base_size = 18) + 
  theme(legend.position = "none") + 
  labs(title = "Trajectories", y = "data score", x = "Wave") +
  geom_errorbar(aes(ymin=score_mean-score_sd, ymax=score_mean+score_sd), width=.2,
                 position=position_dodge(0.05))

示例数据

data_wide <- structure(
    list(ID = c(1, 2, 3, 4, 5, 6), 
    score.baseline = c(4, 4, 5, 4, 6, 4), 
    score.wave1 = c(3.5, 5.67, 5.33, 4, 6.67, 4.5), 
    score.wave2 = c(4, 5, NA, 4, 6.67, 4), 
    score.wave3 = c(6, 6, 4.67, 4.33, 6.67, 3)), 
    row.names = c(1L, 2L, 3L, 4L, 5L, 6L), 
    class = c("data.frame"))

【参考方案1】：

您只需组合代码即可。但是，由于美学是在单个 ggplot 调用中继承的，因此您必须 NULLify 那些在相应层中不需要的部分

ggplot(data_long, aes(x = factor(time), 
                      y = score, 
                      color = as.factor(ID),
                      group = ID)) + 
  geom_line(size = 0.2) + 
  theme_classic(base_size = 18) + 
  theme(legend.position = "none") + 
  labs(title = "Trajectories", y = "data score", x = "Wave") +
  geom_line(data = data_long.group,
            mapping = aes(x = time,
                          y = score_mean,
                          group = NULL, 
                          color = NULL),
            size = 0.2) + 
  theme_classic(base_size = 18) + 
  theme(legend.position = "none") + 
  labs(title = "Trajectories", y = "data score", x = "Wave") +
  geom_errorbar(data = data_long.group, 
                mapping = aes(ymin = score_mean - score_sd,
                              ymax = score_mean + score_sd,
                              y = NULL,
                              group = NULL,
                              color = NULL),
                width = .2,
                position = position_dodge(0.05))