library(knitr)
opts_chunk$set(echo = TRUE )
Package install
Packages <- c("tidyverse", "car","tidyr", "dunn.test","onewaytests","FSA")
lapply(Packages, library, character.only = TRUE)
## -- Attaching packages --------------------------------------------------------------------------------------------------- tidyverse 1.3.0 --
## √ ggplot2 3.2.1 √ purrr 0.3.3
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## √ tidyr 1.0.0 √ stringr 1.4.0
## √ readr 1.3.1 √ forcats 0.4.0
## -- Conflicts ------------------------------------------------------------------------------------------------------ tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
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## Loading required package: carData
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## Attaching package: 'car'
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## ## FSA v0.8.26. See citation('FSA') if used in publication.
## ## Run fishR() for related website and fishR('IFAR') for related book.
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## Attaching package: 'FSA'
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Data import
d1<- read.csv("/Users/koho0/Desktop/hip_fentanyl.csv")
d1 <- gather(d1,time_point,fentanyldose,fentanyl_6:fentanyl_24, factor_key=TRUE)
head(d1)
str(d1)
## 'data.frame': 231 obs. of 4 variables:
## $ id : int 1 2 3 4 5 6 7 8 9 10 ...
## $ group : Factor w/ 3 levels "F","FO","N": 3 1 1 1 3 3 1 1 3 3 ...
## $ time_point : Factor w/ 3 levels "fentanyl_6","fentanyl_12",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ fentanyldose: num 219 385 219 341 211 ...
d1$time_point <-recode(d1$time_point, "'fentanyl_6'='6'")
d1$time_point <-recode(d1$time_point, "'fentanyl_12'='12'")
d1$time_point <-recode(d1$time_point, "'fentanyl_24'='24'")
d1$time_point <-factor(d1$time_point,levels=c("6","12","24"))
p=ggplot(d1,aes(d1[,3],d1[,4],color=group))
p = p + geom_boxplot(outlier.shape = NA) +geom_point(aes(color=group),position=position_dodge(width=0.75))+ ylab("Fentanyl dose(mcg)") +xlab("Time point (hours)") +
theme_bw() +
theme(legend.position = c(0.1,0.9)) +
theme(legend.title = element_blank())
p
