如何通过迭代方法创建一系列带有统计注释的箱线图

2023-12-13

我已经安装了以下模型

models_list_1 <- data_long %>%
  group_by(signals) %>%
  do(fit = lmerTest::lmer(value ~ COND*SES + (1 |ID), data = .)) %>% 
  pull(fit) %>% 
  lapply(., function(x) summary(x)$coefficients) %>%
  setNames(unique(data_long$signals))

并提取成对统计量如下

md <- data_long %>%
  group_by(signals) %>%
  do(fit = lmerTest::lmer(value ~ COND*SES + (1 |ID), data = .)) %>% 
  pull(fit) %>% 
  lapply(., function(m) lsmeans(m, pairwise ~ COND*SES, adjust="tukey"))

如果我想重现迭代地（对于每个signals变量包含在下面的数据集中）一种箱线图

在哪里time报告到示例中，我将得到三个不同的会话（SES = L、V、R）我的数据集（下面将出现报告）以及每个会话之间的一些多重成对比较他们三个状况（COND（NEG-CTR、NEG-NOC 和 NEU-NOC）下面报告到数据集中）我应该做什么？我应该设置哪个以及如何设置迭代函数来报告显着差异条？

提前致谢

这里是数据集

> dput(head(data_long,300))
structure(list(ID = c("01", "01", "01", "01", "01", "01", "01", 
"01", "01", "01", "01", "01", "01", "01", "01", "01", "01", "01", 
"01", "01", "01", "01", "01", "01", "01", "01", "01", "01", "01", 
"01", "01", "01", "01", "01", "01", "01", "01", "01", "01", "01", 
"01", "01", "01", "01", "01", "01", "01", "01", "01", "01", "01", 
"01", "01", "01", "01", "01", "01", "01", "01", "01", "01", "01", 
"01", "01", "01", "01", "01", "01", "01", "01", "01", "01", "01", 
"01", "01", "01", "01", "01", "01", "01", "01", "01", "01", "01", 
"01", "01", "01", "01", "01", "01", "01", "01", "01", "01", "01", 
"01", "01", "01", "01", "01", "01", "01", "01", "01", "01", "01", 
"01", "01", "01", "01", "01", "01", "01", "01", "01", "01", "01", 
"02", "02", "02", "02", "02", "02", "02", "02", "02", "02", "02", 
"02", "02", "02", "02", "02", "02", "02", "02", "02", "02", "02", 
"02", "02", "02", "02", "02", "02", "02", "02", "02", "02", "02", 
"02", "02", "02", "02", "02", "02", "02", "02", "02", "02", "02", 
"02", "02", "02", "02", "02", "02", "02", "02", "02", "02", "02", 
"02", "02", "02", "02", "02", "02", "02", "02", "02", "02", "02", 
"02", "02", "02", "02", "02", "02", "02", "02", "02", "02", "02", 
"02", "04", "04", "04", "04", "04", "04", "04", "04", "04", "04", 
"04", "04", "04", "04", "04", "04", "04", "04", "04", "04", "04", 
"04", "04", "04", "04", "04", "04", "04", "04", "04", "04", "04", 
"04", "04", "04", "04", "04", "04", "04", "04", "04", "04", "04", 
"04", "04", "04", "04", "04", "04", "04", "04", "04", "04", "04", 
"04", "04", "04", "04", "04", "04", "04", "04", "04", "04", "04", 
"04", "04", "04", "04", "04", "04", "04", "04", "04", "04", "04", 
"04", "04", "04", "04", "04", "04", "04", "04", "04", "04", "04", 
"04", "04", "04", "04", "04", "04", "04", "04", "04", "04", "04", 
"04", "04", "04", "04", "04", "04", "04"), GR = c("RP", "RP", 
"RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", 
"RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", 
"RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", 
"RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", 
"RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", 
"RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", 
"RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", 
"RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", 
"RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", 
"RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", 
"RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", 
"RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", 
"RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", 
"RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", 
"RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", 
"RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", 
"RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", 
"RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", 
"RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", 
"RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", 
"RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", 
"RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", 
"RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", 
"RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", 
"RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", 
"RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", 
"RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", "RP", 
"RP"), SES = c("L", "L", "L", "L", "L", "L", "L", "L", "L", "L", 
"L", "L", "L", "L", "L", "L", "L", "L", "L", "L", "L", "L", "L", 
"L", "L", "L", "L", "L", "L", "L", "L", "L", "L", "L", "L", "L", 
"L", "L", "L", "R", "R", "R", "R", "R", "R", "R", "R", "R", "R", 
"R", "R", "R", "R", "R", "R", "R", "R", "R", "R", "R", "R", "R", 
"R", "R", "R", "R", "R", "R", "R", "R", "R", "R", "R", "R", "R", 
"R", "R", "R", "V", "V", "V", "V", "V", "V", "V", "V", "V", "V", 
"V", "V", "V", "V", "V", "V", "V", "V", "V", "V", "V", "V", "V", 
"V", "V", "V", "V", "V", "V", "V", "V", "V", "V", "V", "V", "V", 
"V", "V", "V", "L", "L", "L", "L", "L", "L", "L", "L", "L", "L", 
"L", "L", "L", "L", "L", "L", "L", "L", "L", "L", "L", "L", "L", 
"L", "L", "L", "L", "L", "L", "L", "L", "L", "L", "L", "L", "L", 
"L", "L", "L", "R", "R", "R", "R", "R", "R", "R", "R", "R", "R", 
"R", "R", "R", "R", "R", "R", "R", "R", "R", "R", "R", "R", "R", 
"R", "R", "R", "R", "R", "R", "R", "R", "R", "R", "R", "R", "R", 
"R", "R", "R", "L", "L", "L", "L", "L", "L", "L", "L", "L", "L", 
"L", "L", "L", "L", "L", "L", "L", "L", "L", "L", "L", "L", "L", 
"L", "L", "L", "L", "L", "L", "L", "L", "L", "L", "L", "L", "L", 
"L", "L", "L", "R", "R", "R", "R", "R", "R", "R", "R", "R", "R", 
"R", "R", "R", "R", "R", "R", "R", "R", "R", "R", "R", "R", "R", 
"R", "R", "R", "R", "R", "R", "R", "R", "R", "R", "R", "R", "R", 
"R", "R", "R", "V", "V", "V", "V", "V", "V", "V", "V", "V", "V", 
"V", "V", "V", "V", "V", "V", "V", "V", "V", "V", "V", "V", "V", 
"V", "V", "V", "V"), COND = c("NEG-CTR", "NEG-CTR", "NEG-CTR", 
"NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", 
"NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-NOC", "NEG-NOC", 
"NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", 
"NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", "NEU-NOC", 
"NEU-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", 
"NEU-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", 
"NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", 
"NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", 
"NEG-CTR", "NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", 
"NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", 
"NEG-NOC", "NEG-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", 
"NEU-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", 
"NEU-NOC", "NEU-NOC", "NEU-NOC", "NEG-CTR", "NEG-CTR", "NEG-CTR", 
"NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", 
"NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-NOC", "NEG-NOC", 
"NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", 
"NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", "NEU-NOC", 
"NEU-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", 
"NEU-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", 
"NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", 
"NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", 
"NEG-CTR", "NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", 
"NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", 
"NEG-NOC", "NEG-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", 
"NEU-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", 
"NEU-NOC", "NEU-NOC", "NEU-NOC", "NEG-CTR", "NEG-CTR", "NEG-CTR", 
"NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", 
"NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-NOC", "NEG-NOC", 
"NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", 
"NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", "NEU-NOC", 
"NEU-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", 
"NEU-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", 
"NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", 
"NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", 
"NEG-CTR", "NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", 
"NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", 
"NEG-NOC", "NEG-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", 
"NEU-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", 
"NEU-NOC", "NEU-NOC", "NEU-NOC", "NEG-CTR", "NEG-CTR", "NEG-CTR", 
"NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", 
"NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-NOC", "NEG-NOC", 
"NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", 
"NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", "NEU-NOC", 
"NEU-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", 
"NEU-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", "NEU-NOC", 
"NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", 
"NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", "NEG-CTR", 
"NEG-CTR", "NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", 
"NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", "NEG-NOC", 
"NEG-NOC", "NEG-NOC", "NEU-NOC"), signals = c("P3(400-450).FCz", 
"P3(400-450).Cz", "P3(400-450).Pz", "LPPearly(500-700).FCz", 
"LPPearly(500-700).Cz", "LPPearly(500-700).Pz", "LPP1(500-1000).FCz", 
"LPP1(500-1000).Cz", "LPP1(500-1000).Pz", "LPP2(1000-1500).FCz", 
"LPP2(1000-1500).Cz", "LPP2(1000-1500).Pz", "LPP2(1000-1500).POz", 
"P3(400-450).FCz", "P3(400-450).Cz", "P3(400-450).Pz", "LPPearly(500-700).FCz", 
"LPPearly(500-700).Cz", "LPPearly(500-700).Pz", "LPP1(500-1000).FCz", 
"LPP1(500-1000).Cz", "LPP1(500-1000).Pz", "LPP2(1000-1500).FCz", 
"LPP2(1000-1500).Cz", "LPP2(1000-1500).Pz", "LPP2(1000-1500).POz", 
"P3(400-450).FCz", "P3(400-450).Cz", "P3(400-450).Pz", "LPPearly(500-700).FCz", 
"LPPearly(500-700).Cz", "LPPearly(500-700).Pz", "LPP1(500-1000).FCz", 
"LPP1(500-1000).Cz", "LPP1(500-1000).Pz", "LPP2(1000-1500).FCz", 
"LPP2(1000-1500).Cz", "LPP2(1000-1500).Pz", "LPP2(1000-1500).POz", 
"P3(400-450).FCz", "P3(400-450).Cz", "P3(400-450).Pz", "LPPearly(500-700).FCz", 
"LPPearly(500-700).Cz", "LPPearly(500-700).Pz", "LPP1(500-1000).FCz", 
"LPP1(500-1000).Cz", "LPP1(500-1000).Pz", "LPP2(1000-1500).FCz", 
"LPP2(1000-1500).Cz", "LPP2(1000-1500).Pz", "LPP2(1000-1500).POz", 
"P3(400-450).FCz", "P3(400-450).Cz", "P3(400-450).Pz", "LPPearly(500-700).FCz", 
"LPPearly(500-700).Cz", "LPPearly(500-700).Pz", "LPP1(500-1000).FCz", 
"LPP1(500-1000).Cz", "LPP1(500-1000).Pz", "LPP2(1000-1500).FCz", 
"LPP2(1000-1500).Cz", "LPP2(1000-1500).Pz", "LPP2(1000-1500).POz", 
"P3(400-450).FCz", "P3(400-450).Cz", "P3(400-450).Pz", "LPPearly(500-700).FCz", 
"LPPearly(500-700).Cz", "LPPearly(500-700).Pz", "LPP1(500-1000).FCz", 
"LPP1(500-1000).Cz", "LPP1(500-1000).Pz", "LPP2(1000-1500).FCz", 
"LPP2(1000-1500).Cz", "LPP2(1000-1500).Pz", "LPP2(1000-1500).POz", 
"P3(400-450).FCz", "P3(400-450).Cz", "P3(400-450).Pz", "LPPearly(500-700).FCz", 
"LPPearly(500-700).Cz", "LPPearly(500-700).Pz", "LPP1(500-1000).FCz", 
"LPP1(500-1000).Cz", "LPP1(500-1000).Pz", "LPP2(1000-1500).FCz", 
"LPP2(1000-1500).Cz", "LPP2(1000-1500).Pz", "LPP2(1000-1500).POz", 
"P3(400-450).FCz", "P3(400-450).Cz", "P3(400-450).Pz", "LPPearly(500-700).FCz", 
"LPPearly(500-700).Cz", "LPPearly(500-700).Pz", "LPP1(500-1000).FCz", 
"LPP1(500-1000).Cz", "LPP1(500-1000).Pz", "LPP2(1000-1500).FCz", 
"LPP2(1000-1500).Cz", "LPP2(1000-1500).Pz", "LPP2(1000-1500).POz", 
"P3(400-450).FCz", "P3(400-450).Cz", "P3(400-450).Pz", "LPPearly(500-700).FCz", 
"LPPearly(500-700).Cz", "LPPearly(500-700).Pz", "LPP1(500-1000).FCz", 
"LPP1(500-1000).Cz", "LPP1(500-1000).Pz", "LPP2(1000-1500).FCz", 
"LPP2(1000-1500).Cz", "LPP2(1000-1500).Pz", "LPP2(1000-1500).POz", 
"P3(400-450).FCz", "P3(400-450).Cz", "P3(400-450).Pz", "LPPearly(500-700).FCz", 
"LPPearly(500-700).Cz", "LPPearly(500-700).Pz", "LPP1(500-1000).FCz", 
"LPP1(500-1000).Cz", "LPP1(500-1000).Pz", "LPP2(1000-1500).FCz", 
"LPP2(1000-1500).Cz", "LPP2(1000-1500).Pz", "LPP2(1000-1500).POz", 
"P3(400-450).FCz", "P3(400-450).Cz", "P3(400-450).Pz", "LPPearly(500-700).FCz", 
"LPPearly(500-700).Cz", "LPPearly(500-700).Pz", "LPP1(500-1000).FCz", 
"LPP1(500-1000).Cz", "LPP1(500-1000).Pz", "LPP2(1000-1500).FCz", 
"LPP2(1000-1500).Cz", "LPP2(1000-1500).Pz", "LPP2(1000-1500).POz", 
"P3(400-450).FCz", "P3(400-450).Cz", "P3(400-450).Pz", "LPPearly(500-700).FCz", 
"LPPearly(500-700).Cz", "LPPearly(500-700).Pz", "LPP1(500-1000).FCz", 
"LPP1(500-1000).Cz", "LPP1(500-1000).Pz", "LPP2(1000-1500).FCz", 
"LPP2(1000-1500).Cz", "LPP2(1000-1500).Pz", "LPP2(1000-1500).POz", 
"P3(400-450).FCz", "P3(400-450).Cz", "P3(400-450).Pz", "LPPearly(500-700).FCz", 
"LPPearly(500-700).Cz", "LPPearly(500-700).Pz", "LPP1(500-1000).FCz", 
"LPP1(500-1000).Cz", "LPP1(500-1000).Pz", "LPP2(1000-1500).FCz", 
"LPP2(1000-1500).Cz", "LPP2(1000-1500).Pz", "LPP2(1000-1500).POz", 
"P3(400-450).FCz", "P3(400-450).Cz", "P3(400-450).Pz", "LPPearly(500-700).FCz", 
"LPPearly(500-700).Cz", "LPPearly(500-700).Pz", "LPP1(500-1000).FCz", 
"LPP1(500-1000).Cz", "LPP1(500-1000).Pz", "LPP2(1000-1500).FCz", 
"LPP2(1000-1500).Cz", "LPP2(1000-1500).Pz", "LPP2(1000-1500).POz", 
"P3(400-450).FCz", "P3(400-450).Cz", "P3(400-450).Pz", "LPPearly(500-700).FCz", 
"LPPearly(500-700).Cz", "LPPearly(500-700).Pz", "LPP1(500-1000).FCz", 
"LPP1(500-1000).Cz", "LPP1(500-1000).Pz", "LPP2(1000-1500).FCz", 
"LPP2(1000-1500).Cz", "LPP2(1000-1500).Pz", "LPP2(1000-1500).POz", 
"P3(400-450).FCz", "P3(400-450).Cz", "P3(400-450).Pz", "LPPearly(500-700).FCz", 
"LPPearly(500-700).Cz", "LPPearly(500-700).Pz", "LPP1(500-1000).FCz", 
"LPP1(500-1000).Cz", "LPP1(500-1000).Pz", "LPP2(1000-1500).FCz", 
"LPP2(1000-1500).Cz", "LPP2(1000-1500).Pz", "LPP2(1000-1500).POz", 
"P3(400-450).FCz", "P3(400-450).Cz", "P3(400-450).Pz", "LPPearly(500-700).FCz", 
"LPPearly(500-700).Cz", "LPPearly(500-700).Pz", "LPP1(500-1000).FCz", 
"LPP1(500-1000).Cz", "LPP1(500-1000).Pz", "LPP2(1000-1500).FCz", 
"LPP2(1000-1500).Cz", "LPP2(1000-1500).Pz", "LPP2(1000-1500).POz", 
"P3(400-450).FCz", "P3(400-450).Cz", "P3(400-450).Pz", "LPPearly(500-700).FCz", 
"LPPearly(500-700).Cz", "LPPearly(500-700).Pz", "LPP1(500-1000).FCz", 
"LPP1(500-1000).Cz", "LPP1(500-1000).Pz", "LPP2(1000-1500).FCz", 
"LPP2(1000-1500).Cz", "LPP2(1000-1500).Pz", "LPP2(1000-1500).POz", 
"P3(400-450).FCz", "P3(400-450).Cz", "P3(400-450).Pz", "LPPearly(500-700).FCz", 
"LPPearly(500-700).Cz", "LPPearly(500-700).Pz", "LPP1(500-1000).FCz", 
"LPP1(500-1000).Cz", "LPP1(500-1000).Pz", "LPP2(1000-1500).FCz", 
"LPP2(1000-1500).Cz", "LPP2(1000-1500).Pz", "LPP2(1000-1500).POz", 
"P3(400-450).FCz", "P3(400-450).Cz", "P3(400-450).Pz", "LPPearly(500-700).FCz", 
"LPPearly(500-700).Cz", "LPPearly(500-700).Pz", "LPP1(500-1000).FCz", 
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"P3(400-450).FCz", "P3(400-450).Cz", "P3(400-450).Pz", "LPPearly(500-700).FCz", 
"LPPearly(500-700).Cz", "LPPearly(500-700).Pz", "LPP1(500-1000).FCz", 
"LPP1(500-1000).Cz", "LPP1(500-1000).Pz", "LPP2(1000-1500).FCz", 
"LPP2(1000-1500).Cz", "LPP2(1000-1500).Pz", "LPP2(1000-1500).POz", 
"P3(400-450).FCz", "P3(400-450).Cz", "P3(400-450).Pz", "LPPearly(500-700).FCz", 
"LPPearly(500-700).Cz", "LPPearly(500-700).Pz", "LPP1(500-1000).FCz", 
"LPP1(500-1000).Cz", "LPP1(500-1000).Pz", "LPP2(1000-1500).FCz", 
"LPP2(1000-1500).Cz", "LPP2(1000-1500).Pz", "LPP2(1000-1500).POz", 
"P3(400-450).FCz", "P3(400-450).Cz", "P3(400-450).Pz", "LPPearly(500-700).FCz", 
"LPPearly(500-700).Cz", "LPPearly(500-700).Pz", "LPP1(500-1000).FCz", 
"LPP1(500-1000).Cz", "LPP1(500-1000).Pz", "LPP2(1000-1500).FCz", 
"LPP2(1000-1500).Cz", "LPP2(1000-1500).Pz", "LPP2(1000-1500).POz", 
"P3(400-450).FCz"), value = c(-13.733750856001, -9.75024624896264, 
2.65626156135631, -11.2145748677083, -8.14861856277773, 3.4315211013568, 
-7.774797181711, -5.0379636708446, 4.67200616533014, -0.397250087672501, 
2.91913936481813, 8.38141924882334, 9.61455213192824, -11.0706676917232, 
-8.42427447113084, 3.37360619561252, -13.9481657323772, -11.7645758007163, 
-1.55179922542943, -8.40872060176111, -6.36865552801825, 1.75888442936359, 
1.01519755373062, 1.85489998202138, 4.88842858528025, 7.21299011910717, 
-8.4719202003519, -5.61886494275071, 5.4043480635031, -12.0047623683783, 
-9.16726244915301, 1.13509020104859, -7.03235376576925, -4.54670193355435, 
2.49276476951357, -1.17300033366376, 0.694393606954545, 5.0594399581601, 
6.1861244061312, -5.04318152659785, 0.73152672768007, 19.5226358864568, 
-4.24372139176794, 0.918751423320568, 16.3120391015512, -0.65010821749741, 
4.05493850786385, 13.8997702651793, 0.663115370014327, 3.95694572160701, 
3.88831364571248, 6.46723813995257, -6.25375875400145, 1.11453058993788, 
18.5017390789352, -7.38414465678688, -0.674372568935879, 14.1694182774958, 
-3.24350263682843, 2.67516303169366, 13.2135623121441, -1.72160165493474, 
2.36649557381131, 5.83201076558185, 7.25962635499353, -7.0474968134059, 
-2.25104720773472, 11.7844254386573, -6.61221718491095, -2.47425935490564, 
9.04781409226351, -2.84832379590422, 1.02479302810681, 9.51479768101391, 
0.0540027107377267, 2.71292196345657, 3.65113189260335, 7.92952342178602, 
-11.6312151716924, -5.16524399006139, 11.8802266972569, -11.7785042972793, 
-5.96429031525769, 8.23981597718437, -5.67295796971287, -0.774461731301161, 
9.99385579756163, -0.198736254963744, 2.96437294922766, 6.28027312932027, 
7.91468942320841, -11.1438413285935, -5.53112490175437, 12.1053426662461, 
-9.14927207125904, -5.10918437158799, 9.51261484648731, -4.3918290080777, 
-0.650009462761383, 11.1212652173052, -3.16101041766438, -2.12913230708907, 
5.24535230966772, 9.94838815736199, -3.99591470944713, 0.621502123415388, 
12.955441582096, -7.58190508537766, -2.81732229625975, 9.42367409925817, 
-2.96652960658775, 1.14010250644923, 10.6989716871958, 0.895992279831378, 
2.94619035115619, 7.68162285335806, 10.2186482048953, 8.71618523084192, 
10.0972150696175, 13.9718285231429, 14.2438131545118, 18.1277616996079, 
20.6284861844249, 12.5228696634748, 15.0856583318757, 15.4011622649207, 
9.21248347391488, 10.0673617448764, 8.55827491190151, 5.76901446016799, 
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0.649857280429136, 1.01053594416015, 5.74639215930458, 5.92604591551597, 
5.077230852852, 5.9614279900414, 5.26280996552585, 0.754416368133019, 
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6.04018553841336, 2.18006640865321, 6.61872855398538, 3.66646157996528, 
5.0384350436334, -2.76852389876276, -0.650797837853182, 4.74014346829081, 
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-2.00512841997728, 1.9050381096835, -0.225533814334514, -1.21696526578647, 
0.240956222277802, 0.361670119961531, 5.54144355778122, 7.81248993867768, 
11.9003140352528, -3.32736490042247, -1.77938930999718, 5.40630013085777, 
-0.38736451456005, -0.423105565152366, 6.37211228749408, 0.986467266459687, 
-0.507207892673482, 1.15053325116554, 0.393791410918138, -0.314155675382471, 
2.23100741241039, 15.0981004360619, -4.01515836011381, -1.43557366487622, 
5.06332653216481, 0.159183652691071, 1.51403741206392, 3.7899021820967, 
3.11042068112836, 3.44844607014521, 1.08242973465635, 1.07455889922813, 
0.238885648959708, 3.96990710862955, 15.4046229884164, -6.60165385653499, 
-3.14872157912645, 5.02619159395405, -1.78361184935376, 0.25571835554024, 
4.59413830322224, 2.27800090558473, 3.02403433835637, 2.99896314000211, 
1.65917850515029, 5.03749946898385)), row.names = c(NA, -300L
), class = c("tbl_df", "tbl", "data.frame"))
>

像这样的东西吗？

library(tidyverse)
library(ggpubr)
data_long  %>%
  ggplot(aes(COND, value, color = COND)) +
    geom_boxplot() +
    stat_compare_means(
      comparisons = list(
        c("NEG-CTR", "NEG-NOC"),
        c("NEG-CTR", "NEU-NOC"),
        c("NEG-NOC", "NEU-NOC")
      )
    ) +
    facet_wrap(~signals)

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