library(knitr)
opts_chunk$set(echo = TRUE )
Package install
Packages <- c("tidyverse", "car", "dunn.test","onewaytests","FSA","ggpubr","rcompanion","ggplot2","emmeans","rstatix")
lapply(Packages, library, character.only = TRUE)
## -- Attaching packages --------------------------------------- tidyverse 1.3.1 --
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## ## FSA v0.8.32. See citation('FSA') if used in publication.
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Data import
d1<- read.csv("Fig6_A.LOR_duration_Female.csv")
Data structure
str(d1)
## 'data.frame': 60 obs. of 3 variables:
## $ subject : int 1 2 3 4 5 6 7 8 9 10 ...
## $ inject : chr "1st_inject" "1st_inject" "1st_inject" "1st_inject" ...
## $ duration: int 273 389 120 200 259 305 136 316 192 227 ...
Explorative data analysis with graphics
d1 %>%
group_by(inject) %>%
get_summary_stats(duration, type = "common")
ggboxplot(d1, x = "inject", y = "duration", add = "jitter")
Model fit
res.fried <- d1 %>% friedman_test(duration ~ inject |subject)
res.fried
Effect size
d1 %>% friedman_effsize(duration ~ inject |subject)
Multiple pairwise-comparisons
pwc <- d1 %>%
wilcox_test(duration ~ inject, paired = TRUE, p.adjust.method = "bonferroni")
pwc
sum_test = unlist(res.fried)
names(sum_test)
## [1] ".y." "n"
## [3] "statistic.Friedman chi-squared" "df.df"
## [5] "p" "method"
paov1 = sum_test["p"]
paov1 = sprintf("%.3f",as.numeric(paov1))
Interpretation of result
if (paov1<0.05){
cat("1. The duration was statistically significantly different at the different time points", "\n",
"p =", paov1, "\n")
} else {
cat( "1. The duration was not statistically significantly different at the different time points","\n",
"p =", paov1, "\n" )}
## 1. The duration was statistically significantly different at the different time points
## p = 0.006