Bar Plots
Case Studies
library(tidyverse)
library(readxl)
library(reshape2)
data_case_studies <- read_excel("/Users/ihsanbuker/Desktop/BioAllograft/Data/MRI Data Cleaned.xlsx",
sheet = "Case Studies")
data_case_studies %>%
select(-1,-5,-9) -> data_case_studies
data_case_studies %>%
select(1:3) -> data_case_studies_volume
melt(t(colMeans(data_case_studies_volume))) %>%
select(-1) -> df_volume
colnames(df_volume) <- c("Month", "Mean Volume")
y<-as.matrix(df_volume %>% select(-1))
x<-barplot(df_volume$`Mean Volume`,
main = "Mean Volume ",
ylab = "Mean Volume (mm^3)",
names.arg = c("3 Months", "6 Months", "12 Months"),
horiz = FALSE,
ylim = c(0,3500),
col = "blue")
text(x,y+120,labels=as.character(round(y, digits = 1)))
data_case_studies %>%
select(4:6) -> data_case_studies_T2
melt(t(colMeans(data_case_studies_T2))) %>%
select(-1) -> df_T2
colnames(df_T2) <- c("Month", "Mean T2")
y <- as.matrix(df_T2 %>% select(-1))
x <- barplot(df_T2$`Mean T2`,
main = "Mean T2 ",
ylab = "Mean T2 (ms)",
names.arg = c("3 Months", "6 Months", "12 Months"),
horiz = FALSE,
ylim = c(0,45),
col = "blue")
text(x,y+2,labels=as.character(round(y, digits = 1)))
data_case_studies %>%
select(7:9) -> data_case_studies_T2_star
melt(t(colMeans(data_case_studies_T2_star))) %>%
select(-1) -> df_T2_star
colnames(df_T2_star) <- c("Month", "Mean T2*")
y <- as.matrix(df_T2_star %>% select(-1))
x <- barplot(df_T2_star$`Mean T2*`,
main = "Mean T2* ",
ylab = "Mean T2* (ms)",
names.arg = c("3 Months", "6 Months", "12 Months"),
horiz = FALSE,
ylim = c(0,15),
col = "blue")
text(x,y+0.5,labels=as.character(round(y, digits = 1)))
Allograft
library(tidyverse)
library(readxl)
library(reshape2)
data_allograft <- read_excel("/Users/ihsanbuker/Desktop/BioAllograft/Data/MRI Data Cleaned.xlsx",
sheet = "Allograft")
data_allograft %>%
select(-1,-6,-11) -> data_allograft
data_allograft %>%
select(1:4) -> data_allograft_volume
melt(t(colMeans(data_allograft_volume))) %>%
select(-1) -> df_volume
colnames(df_volume) <- c("Month", "Mean Volume")
y <- as.matrix(df_volume %>% select(-1))
x <- barplot(df_volume$`Mean Volume`,
main = "Mean Volume ",
ylab = "Mean Volume (mm^3)",
names.arg = c("3 Months", "6 Months", "9 Months", "12 Months"),
horiz = FALSE,
xpd = F,
yaxs = "i",
ylim = c(1500,4000),
col = "blue")
text(x,y+100,labels=as.character(round(y, digits = 1)))
data_allograft %>%
select(5:8) -> data_allograft_T2
melt(t(colMeans(data_allograft_T2))) %>%
select(-1) -> df_T2
colnames(df_T2) <- c("Month", "Mean T2")
y <- as.matrix(df_T2 %>% select(-1))
x <- barplot(df_T2$`Mean T2`,
main = "Mean T2 ",
ylab = "Mean T2 (ms)",
names.arg = c("3 Months", "6 Months", "9 Months", "12 Months"),
horiz = FALSE,
ylim = c(30,45),
xpd = FALSE, # if you do not want barplot to spill, set xpd = FALSE
col = "blue")
text(x,y+0.5,labels=as.character(round(y, digits = 1)))
data_allograft %>%
select(9:12) -> data_allograft_T2_star
melt(t(colMeans(data_allograft_T2_star))) %>%
select(-1) -> df_T2_star
colnames(df_T2_star) <- c("Month", "Mean T2*")
y <- as.matrix(df_T2_star %>% select(-1))
x <- barplot(df_T2_star$`Mean T2*`,
main = "Mean T2* ",
ylab = "Mean T2* (ms)",
names.arg = c("3 Months", "6 Months", "9 Months", "12 Months"),
horiz = FALSE,
ylim = c(5,15),
yaxs = "i",
xpd = F,
col = "blue")
text(x,y+0.27,labels=as.character(round(y, digits = 1)))
Hamstring
library(rlist)
library(readxl)
library(readr)
library(tidyverse)
data_hamstring <- read_excel("/Users/ihsanbuker/Desktop/BioAllograft/Data/MRI Data Cleaned.xlsx",
sheet = "Hamstring")
data_hamstring %>%
select(-1,-3,-8,-13) -> data_hamstring
# Volume Data
data_hamstring %>%
select(1,2:5) %>%
group_by(data_hamstring$Group, .add = TRUE) %>%
group_split() -> x
x[[1]] %>%
select(-6) -> df_volume_control
control <- as.data.frame(colMeans(df_volume_control %>% select(-1)))
control$Group <- "Control"
control$Month <- row.names(control)
row.names(control) <- NULL
colnames(control) <- c("Mean Volume", "Group", "Month")
x[[2]] %>%
select(-6) -> df_volume_intervention
intervention <- as.data.frame(colMeans(df_volume_intervention %>% select(-1)))
intervention$Group <- "Intervention"
intervention$Month <- row.names(intervention)
row.names(intervention) <- NULL
colnames(intervention) <- c("Mean Volume", "Group", "Month")
df_volume <- rbind(intervention,control)
df_volume %>%
group_by(Month) %>%
group_split() -> y
y[[2]] %>% select(-3,-2) -> three_months
y[[3]] %>% select(-3,-2) -> six_months
y[[4]] %>% select(-3,-2) -> nine_months
y[[1]] %>% select(-3,-2) -> twelve_months
z <- cbind(three_months, six_months, nine_months, twelve_months)
z$Group <- c("Intervention", "Control")
colnames(z) <- c("3 Months", "6 Months", "9 Months", "12 Months", "Group")
s <- as.matrix(data.matrix(z))
y <- s[c(-9,-10)]
x <- barplot(s,
beside = T,
xlim = c(1,12),
xpd = F,
ylim = c(2000,4000),
main = "Mean Volume ",
ylab = "Mean Volume (mm^3)",
col = c("blue", "red"))
legend("topright",legend = c("Intervention","Control"), fill = c("blue","red"), horiz = T, cex = 0.7)
text(x,y+85,labels=as.character(round(y, digits = 1)), cex = 0.8)
# T2 Data
data_hamstring %>%
select(1,6:9) %>%
group_by(data_hamstring$Group, .add = TRUE) %>%
group_split() -> x
x[[1]] %>%
select(-6) -> df_T2_control
control <- as.data.frame(colMeans(df_T2_control %>% select(-1)))
control$Group <- "Control"
control$Month <- row.names(control)
row.names(control) <- NULL
colnames(control) <- c("Mean T2", "Group", "Month")
x[[2]] %>%
select(-6) -> df_T2_intervention
intervention <- as.data.frame(colMeans(df_T2_intervention %>% select(-1)))
intervention$Group <- "Intervention"
intervention$Month <- row.names(intervention)
row.names(intervention) <- NULL
colnames(intervention) <- c("Mean T2", "Group", "Month")
df_volume <- rbind(intervention,control)
df_volume %>%
group_by(Month) %>%
group_split() -> y
y[[2]] %>% select(-3,-2) -> three_months
y[[3]] %>% select(-3,-2) -> six_months
y[[4]] %>% select(-3,-2) -> nine_months
y[[1]] %>% select(-3,-2) -> twelve_months
z <- cbind(three_months, six_months, nine_months, twelve_months)
z$Group <- c("Intervention", "Control")
colnames(z) <- c("3 Months", "6 Months", "9 Months", "12 Months", "Group")
s <-as.matrix(data.matrix(z))
y <- s[c(-9,-10)]
x <- barplot(s,
beside = T,
xlim = c(1,12),
ylim = c(20,45),
xpd = F,
main = "Mean T2 ",
ylab = "Mean T2 (ms)",
col = c("blue", "red"))
legend("topright",legend = c("Intervention","Control"), fill = c("blue","red"), horiz = T, cex = 0.7)
text(x,y+1,labels=as.character(round(y, digits = 1)), cex = 0.8)
# T2* Data
data_hamstring %>%
select(1,10:13) %>%
group_by(data_hamstring$Group, .add = TRUE) %>%
group_split() -> x
x[[1]] %>%
select(-6) -> df_T2_star_control
control <- as.data.frame(colMeans(df_T2_star_control %>% select(-1)))
control$Group <- "Control"
control$Month <- row.names(control)
row.names(control) <- NULL
colnames(control) <- c("Mean T2_star", "Group", "Month")
x[[2]] %>%
select(-6) -> df_T2_star_intervention
intervention <- as.data.frame(colMeans(df_T2_star_intervention %>% select(-1)))
intervention$Group <- "Intervention"
intervention$Month <- row.names(intervention)
row.names(intervention) <- NULL
colnames(intervention) <- c("Mean T2_star", "Group", "Month")
df_volume <- rbind(intervention,control)
df_volume %>%
group_by(Month) %>%
group_split() -> y
y[[2]] %>% select(-3,-2) -> three_months
y[[3]] %>% select(-3,-2) -> six_months
y[[4]] %>% select(-3,-2) -> nine_months
y[[1]] %>% select(-3,-2) -> twelve_months
z <- cbind(three_months, six_months, nine_months, twelve_months)
z$Group <- c("Intervention", "Control")
colnames(z) <- c("3 Months", "6 Months", "9 Months", "12 Months", "Group")
s<-as.matrix(data.matrix(z))
y <-s[c(-9,-10)]
x <- barplot(s,
beside = T,
xlim = c(1,12),
ylim = c(6,15),
xpd = F,
main = "Mean T2* ",
ylab = "Mean T2* (ms)",
col = c("blue", "red"))
legend("topright",legend = c("Intervention","Control"), fill = c("blue","red"), horiz = T, cex = 0.7)
text(x,y+0.5,labels=as.character(round(y, digits = 1)), cex = 0.8)
BTB
library(readxl)
library(tidyverse)
data_BTB <- read_excel("/Users/ihsanbuker/Desktop/BioAllograft/Data/MRI Data Cleaned.xlsx",
sheet = "BTB")
data_BTB %>%
select(-1,-3,-8,-13) -> data_BTB
# Volume Data
data_BTB %>%
select(1,2:5) %>%
group_by(data_BTB$Group, .add = TRUE) %>%
group_split() -> x
x[[1]] %>%
select(-6) -> df_volume_control
control <- as.data.frame(colMeans(df_volume_control %>% select(-1)))
control$Group <- "Control"
control$Month <- row.names(control)
row.names(control) <- NULL
colnames(control) <- c("Mean volume", "Group", "Month")
x[[2]] %>%
select(-6) -> df_volume_intervention
intervention <- as.data.frame(colMeans(df_volume_intervention %>% select(-1)))
intervention$Group <- "Intervention"
intervention$Month <- row.names(intervention)
row.names(intervention) <- NULL
colnames(intervention) <- c("Mean volume", "Group", "Month")
df_volume <- rbind(intervention,control)
df_volume %>%
group_by(Month) %>%
group_split() -> y
y[[2]] %>% select(-3,-2) -> three_months
y[[3]] %>% select(-3,-2) -> six_months
y[[4]] %>% select(-3,-2) -> nine_months
y[[1]] %>% select(-3,-2) -> twelve_months
z <- cbind(three_months, six_months, nine_months, twelve_months)
z$Group <- c("Intervention", "Control")
colnames(z) <- c("3 Months", "6 Months", "9 Months", "12 Months", "Group")
s <-as.matrix(data.matrix(z))
y <- s[c(-9,-10)]
x <- barplot(s,
beside = T,
xlim = c(1,12),
ylim = c(1500,3500),
yaxs = "i",
xpd = F,
main = "Mean Volume ",
ylab = "Mean Volume (mm^3)",
col = c("blue", "red"))
legend("topright",legend = c("Intervention","Control"), fill = c("blue","red"), horiz = T, cex = 0.7)
text(x,y+85,labels=as.character(round(y, digits = 1)), cex = 0.8)
# T2 Data
data_BTB %>%
select(1,6:9) %>%
group_by(data_BTB$Group, .add = TRUE) %>%
group_split() -> x
x[[1]] %>%
select(-6) -> df_T2_control
control <- as.data.frame(colMeans(df_T2_control %>% select(-1)))
control$Group <- "Control"
control$Month <- row.names(control)
row.names(control) <- NULL
colnames(control) <- c("Mean T2", "Group", "Month")
x[[2]] %>%
select(-6) -> df_T2_intervention
intervention <- as.data.frame(colMeans(df_T2_intervention %>% select(-1)))
intervention$Group <- "Intervention"
intervention$Month <- row.names(intervention)
row.names(intervention) <- NULL
colnames(intervention) <- c("Mean T2", "Group", "Month")
df_T2 <- rbind(intervention,control)
df_T2 %>%
group_by(Month) %>%
group_split() -> y
y[[2]] %>% select(-3,-2) -> three_months
y[[3]] %>% select(-3,-2) -> six_months
y[[4]] %>% select(-3,-2) -> nine_months
y[[1]] %>% select(-3,-2) -> twelve_months
z <- cbind(three_months, six_months, nine_months, twelve_months)
z$Group <- c("Intervention", "Control")
colnames(z) <- c("3 Months", "6 Months", "9 Months", "12 Months", "Group")
s<-as.matrix(data.matrix(z))
y <- s[c(-9,-10)]
x<-barplot(s,
beside = T,
xlim = c(1,12),
ylim = c(20,45),
yaxs = "i",
xpd = F,
main = "Mean T2 ",
ylab = "Mean T2 (ms)",
col = c("blue", "red"))
legend("topright",legend = c("Intervention","Control"), fill = c("blue","red"), horiz = T, cex = 0.7)
text(x,y+1,labels=as.character(round(y, digits = 1)), cex = 0.8)
# T2* Data
data_BTB %>%
select(1,10:13) %>%
group_by(data_BTB$Group, .add = TRUE) %>%
group_split() -> x
x[[1]] %>%
select(-6) -> df_T2_star_control
control <- as.data.frame(colMeans(df_T2_star_control %>% select(-1)))
control$Group <- "Control"
control$Month <- row.names(control)
row.names(control) <- NULL
colnames(control) <- c("Mean T2_star", "Group", "Month")
x[[2]] %>%
select(-6) -> df_T2_star_intervention
intervention <- as.data.frame(colMeans(df_T2_star_intervention %>% select(-1)))
intervention$Group <- "Intervention"
intervention$Month <- row.names(intervention)
row.names(intervention) <- NULL
colnames(intervention) <- c("Mean T2_star", "Group", "Month")
df_T2_star <- rbind(intervention,control)
df_T2_star %>%
group_by(Month) %>%
group_split() -> y
y[[2]] %>% select(-3,-2) -> three_months
y[[3]] %>% select(-3,-2) -> six_months
y[[4]] %>% select(-3,-2) -> nine_months
y[[1]] %>% select(-3,-2) -> twelve_months
z <- cbind(three_months, six_months, nine_months, twelve_months)
z$Group <- c("Intervention", "Control")
colnames(z) <- c("3 Months", "6 Months", "9 Months", "12 Months", "Group")
s<-as.matrix(data.matrix(z))
y <- s[c(-9,-10)]
x <- barplot(s,
beside = T,
xlim = c(1,12),
ylim = c(0,20),
yaxs = "i",
xpd = F,
main = "Mean T2* ",
ylab = "Mean T2* (ms)",
col = c("blue", "red"))
legend("topright",legend = c("Intervention","Control"), fill = c("blue","red"), horiz = T, cex = 0.7)
text(x,y+1,labels=as.character(round(y, digits = 1)), cex = 0.8)
Line Plots
Case Studies
library(tidyverse)
library(readxl)
data_case_studies <- read_excel("/Users/ihsanbuker/Desktop/BioAllograft/Data/MRI Data Cleaned.xlsx",
sheet = "Case Studies")
data_case_studies <- data_case_studies %>%
select(-1,-5,-9)
data_case_studies_volume <- data_case_studies %>%
select(1:3)
plot(colMeans(data_case_studies_volume), type = "b",
xaxt = "n",
ylab = "Mean Volume (mm^3)",
main = "Mean Volume (mm^3)",)
text((c(1.15,2.2,2.87)),colMeans(data_case_studies_volume),
labels=round(colMeans(data_case_studies_volume),
digits = 1),
cex = 0.7)
axis(1, at = 1:3,labels = c("3 Months", "6 Months", "12 Months") )
data_case_studies_T2ms <- data_case_studies %>%
select(4:6)
plot(colMeans(data_case_studies_T2ms), type = "b",
xlab = "",
xaxt = "n",
ylab = "Mean T2 (ms)",
main = "Mean T2 (ms)")
text((c(1.15,2.1,2.9)),colMeans(data_case_studies_T2ms),
labels=round(colMeans(data_case_studies_T2ms),
digits = 1),
cex = 0.7)
axis(1, at = 1:3,labels = c("3 Months", "6 Months", "12 Months") )
data_case_studies_T2ms_star <- data_case_studies %>%
select(7:9)
plot(colMeans(data_case_studies_T2ms_star), type = "b",
xlab = "",
xaxt = "n",
ylab = "Mean T2* (ms)",
main = "Mean T2* (ms)")
text((c(1.1,2.1,2.9)),colMeans(data_case_studies_T2ms_star),
labels=round(colMeans(data_case_studies_T2ms_star),
digits = 1),
cex = 0.7)
axis(1, at = 1:3,labels = c("3 Months", "6 Months", "12 Months") )
Allograft
library(tidyverse)
library(readxl)
data_allograft <- read_excel("/Users/ihsanbuker/Desktop/BioAllograft/Data/MRI Data Cleaned.xlsx",
sheet = "Allograft")
# Removes empty columns and ids.
data_allograft <- data_allograft %>%
select(-1,-6,-11)
data_allograft_volume <- data_allograft %>%
select(1:4)
plot(colMeans(data_allograft_volume), type = "b",
xlab = "",
xaxt = "n",
ylab = "Mean Volume (mm^3)",
main = "Mean Volume (mm^3)")
text((c(1.2,2.3,2.8,3.8)),((colMeans(data_allograft_volume))),
labels=round(colMeans(data_allograft_volume),
digits = 1),
cex = 0.7)
axis(1, at = 1:4,labels = c("3 Months", "6 Months","9 Months", "12 Months"))
data_allograft_T2ms <- data_allograft %>%
select(5:8)
plot(colMeans(data_allograft_T2ms), type = "b",
xlab = "",
ylab = "Mean T2 (ms)",
xaxt = "n",
main = "Mean T2 (ms)")
text((c(1.2,2.2,2.8,3.8)),colMeans(data_allograft_T2ms),
labels=round(colMeans(data_allograft_T2ms),
digits = 1),
cex = 0.7)
axis(1, at = 1:4,labels = c("3 Months", "6 Months","9 Months", "12 Months"))
data_allograft_T2ms_star <- data_allograft %>%
select(9:12)
plot(colMeans(data_allograft_T2ms_star), type = "b",
xlab = "",
ylab = "Mean T2* (ms)",
xaxt = "n",
main = "Mean T2* (ms)")
text((c(1.1,2.1,2.85,3.9)),colMeans(data_allograft_T2ms_star),
labels=round(colMeans(data_allograft_T2ms_star),
digits = 1),
cex = 0.7)
axis(1, at = 1:4,labels = c("3 Months", "6 Months","9 Months", "12 Months"))
Hamstring
library(readxl)
library(readxl)
data_hamstring <- read_excel("/Users/ihsanbuker/Desktop/BioAllograft/Data/MRI Data Cleaned.xlsx",
sheet = "Hamstring")
data_hamstring <- data_hamstring %>%
select(-1,-3,-8,-13)
data_hamstring_volume <- data_hamstring %>%
select(1:5)
df <- data_hamstring_volume %>%
group_by(data_hamstring_volume$Group) %>%
group_split()
df_control <- df[[1]] %>%
select(2:5)
df_intervention <- df[[2]] %>%
select(2:5)
plot(colMeans(df_control), type = "b",
xlab = "",
main = "Mean Volume (mm^3)",
xaxt = "n",
ylim = c(2800,3300),
ylab = "Mean Volume (mm^3)",
col = "red")
text((c(1.2,2.3,2.8,3.64)),colMeans(df_control),
labels=round(colMeans(df_control),
digits = 1),
cex = 0.7, col = "red")
lines(colMeans(df_intervention), type = "b", col = "blue")
text((c(1.3,1.8,3.2,3.9)),colMeans(df_intervention),
labels=round(colMeans(df_intervention),
digits = 1),
cex = 0.7, col = "blue")
legend(2.5,3100, legend = c("Control", "Intervention"), col = c("red", "blue"), lty = 1)
axis(1, at = 1:4,labels = c("3 Months", "6 Months","9 Months", "12 Months"))
data_hamstring_T2 <- data_hamstring %>%
select(1,6:9)
df <- data_hamstring_T2 %>%
group_by(data_hamstring_T2$Group) %>%
group_split()
df_control <- df[[1]] %>%
select(2:5)
df_intervention <- df[[2]] %>%
select(2:5)
plot(colMeans(df_control), type = "b",
main = "Mean T2 (ms)",
xaxt = "n",
xlab = "",
ylab = "Mean T2 (ms)",
col = "red")
text((c(1.2,2.3,2.8,3.64)),colMeans(df_control),
labels=round(colMeans(df_control),
digits = 1),
cex = 0.7, col = "red")
lines(colMeans(df_intervention), type = "b", col = "blue")
text((c(1.3,1.8,3.2,3.8)),colMeans(df_intervention),
labels=round(colMeans(df_intervention),
digits = 1),
cex = 0.7, col = "blue")
legend(2.49,45.5, legend = c("Control", "Intervention"), col = c("red", "blue"), lty = 1)
axis(1, at = 1:4,labels = c("3 Months", "6 Months","9 Months", "12 Months"))
data_hamstring_T2_star <- data_hamstring %>%
select(1,10:13)
df <- data_hamstring_T2_star %>%
group_by(data_hamstring_T2_star$Group) %>%
group_split()
df_control <- df[[1]] %>%
select(2:5)
df_intervention <- df[[2]] %>%
select(2:5)
plot(colMeans(df_control), type = "b",
ylim = c(9,13),
main = "Mean T2*",
xaxt = "n",
xlab = "",
ylab = "Mean T2* (ms)",
col = "red")
text((c(1.2,2.3,2.8,3.64)),colMeans(df_control),
labels=round(colMeans(df_control),
digits = 1),
cex = 0.7, col = "red")
lines(colMeans(df_intervention), type = "b", col = "blue")
text((c(1.3,1.8,3.2,3.8)),colMeans(df_intervention),
labels=round(colMeans(df_intervention),
digits = 1),
cex = 0.7, col = "blue")
legend(2.49,13, legend = c("Control", "Intervention"), col = c("red", "blue"), lty = 1)
axis(1, at = 1:4,labels = c("3 Months", "6 Months","9 Months", "12 Months"))
BTB
library(readxl)
library(tidyverse)
data_BTB <- read_excel("/Users/ihsanbuker/Desktop/BioAllograft/Data/MRI Data Cleaned.xlsx",
sheet = "BTB")
data_BTB <- data_BTB %>%
select(-1,-3,-8,-13)
data_BTB_volume <- data_BTB %>%
select(1:5)
df <- data_BTB_volume %>%
group_by(data_BTB_volume$Group) %>%
group_split()
df_control <- df[[1]] %>%
select(2:5)
df_intervention <- df[[2]] %>%
select(2:5)
plot(colMeans(df_control), type = "b",
ylim = c(2000,3000),
main = "Mean Volume (mm^3)",
xaxt = "n",
xlab = "",
ylab = "Mean Volume (mm^3)",
col = "red")
text((c(1.2,2.3,2.8,3.64)),colMeans(df_control),
labels=round(colMeans(df_control),
digits = 1),
cex = 0.7, col = "red")
lines(colMeans(df_intervention), type = "b", col = "blue")
text((c(1.3,1.8,3.2,3.8)),colMeans(df_intervention),
labels=round(colMeans(df_intervention),
digits = 1),
cex = 0.7, col = "blue")
legend(2,2700, legend = c("Control", "Intervention"), col = c("red", "blue"), lty = 1)
axis(1, at = 1:4,labels = c("3 Months", "6 Months","9 Months", "12 Months"))
data_BTB_T2 <- data_BTB %>%
select(1,6:9)
# Separates control and intervention groups.
df <- data_BTB_T2 %>%
group_by(data_BTB_T2$Group) %>%
group_split()
df_control <- df[[1]] %>%
select(2:5)
df_intervention <- df[[2]] %>%
select(2:5)
plot(colMeans(df_control), type = "b",
ylim = c(30,40),
main = "Mean T2 (ms)",
xaxt = "n",
xlab = "",
ylab = "Mean T2 (ms)",
col = "red")
text((c(1.2,2.3,2.8,3.64)),colMeans(df_control),
labels=round(colMeans(df_control),
digits = 1),
cex = 0.7, col = "red")
lines(colMeans(df_intervention), type = "b", col = "blue")
text((c(1.3,1.8,3.2,3.8)),colMeans(df_intervention),
labels=round(colMeans(df_intervention),
digits = 1),
cex = 0.7, col = "blue")
legend(2.49,39, legend = c("Control", "Intervention"), col = c("red", "blue"), lty = 1)
axis(1, at = 1:4,labels = c("3 Months", "6 Months","9 Months", "12 Months"))
data_BTB_T2_star <- data_BTB %>%
select(1,10:13)
df <- data_BTB_T2_star %>%
group_by(data_BTB_T2_star$Group) %>%
group_split()
df_control <- df[[1]] %>%
select(2:5)
df_intervention <- df[[2]] %>%
select(2:5)
plot(colMeans(df_control), type = "b",
ylim = c(8.5,12),
xaxt = "n",
main = "Mean T2* (ms)",
xlab = "",
ylab = "Mean T2* (ms)",
col = "red")
text((c(1.2,2.3,2.8,3.64)),colMeans(df_control),
labels=round(colMeans(df_control),
digits = 1),
cex = 0.7, col = "red")
lines(colMeans(df_intervention), type = "b", col = "blue")
text((c(1.3,1.8,3.2,3.8)),colMeans(df_intervention),
labels=round(colMeans(df_intervention),
digits = 1),
cex = 0.7, col = "blue")
legend(1,11.5, legend = c("Control", "Intervention"), col = c("red", "blue"), lty = 1)
axis(1, at = 1:4,labels = c("3 Months", "6 Months","9 Months", "12 Months"))
