如何通过迭代方法创建一系列带有统计注释的箱线图 [英] How to create by an iterative method a series of boxplots with statistics annotations

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问题描述

I've fitted the following model

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))

and extracted the pairwise stastistics as follows

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"))

If I would like to reprocude iteratively (for each of signals variable included into the dataset below) a kind of boxplots graph

where in the place of time reported into the example, I will have the three different sessions (SES = L,V,R) of my dataset (reported below will appear) and for each sessions some multiple pairwise comparisons among the three conditions (COND (NEG-CTR, NEG-NOC and NEU-NOC) reported below into the dataset) what am I supposed to do? Which and how I should set an iterative function for reporting the bar of significant difference?

Thanks in advance

Here the dataset

> 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", 
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"LPP2(1000-1500).Cz", "LPP2(1000-1500).Pz", "LPP2(1000-1500).POz", 
"P3(400-450).FCz"), value = c(-13.733750856001, -9.75024624896264, 
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2.23100741241039, 15.0981004360619, -4.01515836011381, -1.43557366487622, 
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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"))
>

解决方案

Something like this?

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)

这篇关于如何通过迭代方法创建一系列带有统计注释的箱线图的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！

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