如何绘制连接geom_points的线以用于R中的重复测量？

Question

我正在寻找一种方法来连接我的 ggplot 中的各个数据点，以便表明数据是随着时间的推移对同一个人的重复测量。 到目前为止，我已经成功地创建了一个条形图，上面有单独的 geom_point（每个主题的数据点）。 但是，我想将三个时间点之间与同一参与者匹配的点连接起来。 任何指针？

  ## Example data, data from two groups: patients and controls
    data_ex <- data.frame( pnum = c(1,2,3,4,5,6,7,8,9,10),
                               group = c("patient", "patient","patient","patient","patient","control","control","control", "control", "control"),
                               age = c(24,35,43,34,55,24,36,43,34,54),
                               panas_1.1 = c(-26, -15, -17, -15, -20, -21, -18, -19, -16, -20),
                               panas_1.2 = c(-25, -19, -14, -18, -20, -22, -17, -19, -18, -19),
                               panas_1.3 = c(-22, -21, -18, -14, -21, -21, -14, -17, -16, -18))

    ## Reshape the data
        data_ex_long <- data_ex %>% gather(key = time, value = PANAS_score, panas_1.1, panas_1.2, panas_1.3)

    ## plot the data
        ggplot(data=data_ex_long,aes(x = time, y = PANAS_score, fill = group)) +  
            geom_bar(stat = "summary",fun.y = 'mean', colour="black", size=1.8, position = position_dodge(width = 1)) +
          geom_point(aes(time, fill = group), colour="black", size = 3, shape = 21, position = 
                       position_jitterdodge(jitter.width = 0.2, jitter.height=0.4, 
                                            dodge.width=0.9), alpha = 0.8) +
          geom_errorbar(aes(size=2),stat = 'summary', position = 'dodge', color = "black", width = 1, size = 1, fatten = 2) +
          theme(text = element_text(size = 18),
                legend.position = "none",
                axis.text.x  = element_text(size=15, color="#000000"),     
                axis.text.y  = element_text(size=20, color="#000000"),       
                axis.title.x = element_blank(),  
                axis.title.y = element_text(size=18, color="#000000"),
                axis.line.x  = element_line(colour = "black", size = 1.3), 
                axis.line.y  = element_line(colour = "black", size = 1.3),
                panel.border = element_blank(),
                panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
                panel.grid.minor.x = element_blank(), panel.grid.major.x = element_blank(),
                panel.background = element_blank(),
                axis.ticks.length = unit(.25, "cm"),
                axis.line = element_line()) +
          ylab(" PANAS score ") + 
          NULL

Answer 1

你可以试试

pd <- position_dodge(0.8)
ggplot(data=data_ex_long,aes(x = time, y = PANAS_score, fill = factor(group, levels = c("patient", "control")))) +  
  geom_bar(stat = "summary",fun.y = 'mean', color=1, position = "dodge") +
  geom_point(aes(group=pnum),position = pd, shape =21) +
  geom_line(aes(group=pnum),position = pd) + 
  geom_errorbar(stat = 'summary', position = "dodge") +
  scale_fill_discrete("")

根据您的评论，我建议完全切换到stat_summary

pd <- position_dodge(.9)

data_ex_long$group <- factor(data_ex_long$group, levels = c("patient", "control"))
ggplot(data=data_ex_long,aes(x = time, y = PANAS_score, fill = group)) +  
  stat_summary(fun.y = "mean", geom = "bar",position = pd) + 
  stat_summary(aes(group = group), 
               fun.y = "mean", geom = "line",position = pd, size= 1.5 ) + 
  stat_summary(fun.data = mean_se, geom = "errorbar",position = pd, width = 0.3) + 
  geom_point(aes(group=pnum),position = pd, shape =21)

使用ggplot2_3.1.0

Answer 2

我正在尝试做类似的情节，但正在努力！ 我有两个重复测量因素，而不是一个重复测量和独立的小组。 因此，在我的x轴上，我有一个之前和之后的药物测量值，前两个框图（静止与动作的颜色不同），后两个框图（不同颜色的静止与动作的坐标）。 我希望能够显示每个主题的趋势，四个4个图中每个图都有一个数据点。

以下是箱形图，每个箱形图带有抖动点，但是我想用一条线连接各个主题的点。

p <- ggplot(df, aes(x=Group, y=PLV, fill=Move)) +
  geom_boxplot(outlier.size = -1) +
  geom_point(df,mapping=aes(x=Group, y=PLV, fill=Move), position = position_jitterdodge  0.2)

df：

1   Before  Rest    0.22238
2   Before  Rest    0.21670
3   Before  Rest    0.21443
4   Before  Rest    0.22624
5   Before  Move    0.22796
6   Before  Move    0.22217
7   Before  Move    0.21418
8   Before  Move    0.21679
9   After   Rest    0.36057
10  After   Rest    0.26613
11  After   Rest    0.27747
12  After   Rest    0.32213
13  After   Move    0.35226
14  After   Move    0.27122
15  After   Move    0.26650
16  After   Move    0.28785