Histograms

# Load packages

library('cowplot') 
library('ggplot2') 

# Visualising small effect size
ES <- 0.25
mean1 <- ES*1 + 1
x <- seq(1 - 3*1, mean1 + 3*1, .01)
y1 <- dnorm(x, 1, 1)
df1 <- data.frame("x" = x, "y" = y1)
y2 <- dnorm(x, mean1, 1)
df2 <- data.frame("x" = x, "y" = y2)
y.poly <- pmin(y1,y2)
poly <- data.frame("x" = x, "y" = y.poly)

u3 <- 1 - pnorm(1, mean1,1)
u3 <- round(u3,3)

fig1a <- ggplot(df1, aes(x,y, color="treatment")) +
  geom_line(size=1) + 
  geom_line(data=df2, aes(color="control"),size=1) +
  geom_polygon(aes(color=NULL), data=poly, fill="red", alpha=I(4/10),
               show.legend=FALSE) +
  geom_vline(xintercept = 1, linetype="dotted") + 
  geom_vline(xintercept = mean1, linetype="dotted") + 
  scale_color_manual("Group", 
                     values= c("treatment" = "black","control" = "red")) +
  ylab(NULL) + xlab(NULL) +
  scale_fill_discrete(name="Group", 
                      breaks=c("control", "treatment"),
                      labels=c("Control group", "Case group")) + 
  theme(legend.position="none")
fig1a <- fig1a + theme(axis.text.x  = element_text(size=24),
                       axis.text.y  = element_text(size=24))

# Visualising medium effect size
ES <- 0.5
mean1 <- ES*1 + 1
x <- seq(1 - 3*1, mean1 + 3*1, .01)
y1 <- dnorm(x, 1, 1)
df1 <- data.frame("x" = x, "y" = y1)
y2 <- dnorm(x, mean1, 1)
df2 <- data.frame("x" = x, "y" = y2)
y.poly <- pmin(y1,y2)
poly <- data.frame("x" = x, "y" = y.poly)

u3 <- 1 - pnorm(1, mean1,1)
u3 <- round(u3,3)

fig1b <- ggplot(df1, aes(x,y, color="treatment")) +
  geom_line(size=1) + 
  geom_line(data=df2, aes(color="control"),size=1) +
  geom_polygon(aes(color=NULL), data=poly, fill="red", alpha=I(4/10),
               show.legend=FALSE) +
  geom_vline(xintercept = 1, linetype="dotted") + 
  geom_vline(xintercept = mean1, linetype="dotted") + 
  scale_color_manual("Group", 
                     values= c("treatment" = "black","control" = "red")) +
  ylab(NULL) + xlab(NULL) +
  scale_fill_discrete(name="Group", 
                      breaks=c("control", "treatment"),
                      labels=c("Control group", "Case group")) + 
  theme(legend.position="none")
fig2b <- fig2b + theme(axis.text.x  = element_text(size=24),
                       axis.text.y  = element_text(size=24))

# Visualising large effect size
ES <- 0.75
mean1 <- ES*1 + 1
x <- seq(1 - 3*1, mean1 + 3*1, .01)
y1 <- dnorm(x, 1, 1)
df1 <- data.frame("x" = x, "y" = y1)
y2 <- dnorm(x, mean1, 1)
df2 <- data.frame("x" = x, "y" = y2)
y.poly <- pmin(y1,y2)
poly <- data.frame("x" = x, "y" = y.poly)

u3 <- 1 - pnorm(1, mean1,1)
u3 <- round(u3,3)

fig1c <- ggplot(df1, aes(x,y, color="treatment")) +
  geom_line(size=1) + 
  geom_line(data=df2, aes(color="control"),size=1) +
  geom_polygon(aes(color=NULL), data=poly, fill="red", alpha=I(4/10),
               show.legend=FALSE) +
  geom_vline(xintercept = 1, linetype="dotted") + 
  geom_vline(xintercept = mean1, linetype="dotted") + 
  scale_color_manual("Group", 
                     values= c("treatment" = "black","control" = "red")) +
  ylab(NULL) + xlab(NULL) +
  scale_fill_discrete(name="Group", 
                      breaks=c("control", "treatment"),
                      labels=c("Control group", "Case group")) + 
  theme(legend.position="none")
fig1c <- fig1c + theme(axis.text.x  = element_text(size=24),
                       axis.text.y  = element_text(size=24))

fig1 <- plot_grid(fig1a, fig1b, fig1c, labels = c("A", "B", "C"),  ncol = 3)
save_plot("fighist.jpg", fig1, base_height = 8, base_width = 20)