#Two group estimation stats plot
#Data has one column that is a text vector denoting group (Control, Treatment; here: x)
#And a second column with continuous outcome (here: y)

library(dabestr)

unpaired_meandiff<-dabest(dabestdat, x, y, paired = FALSE,
                          idx=c("control","treatment")) %>%
  mean_diff(ci = 95, reps = 5000, seed = 12345) #reps and seed refer to bootstrapping

# Display the results in a user-friendly format.
unpaired_meandiff

## dabestr (Data Analysis with Bootstrap Estimation in R) v0.3.0
## =============================================================
## 
## Good afternoon!
## The current time is 16:40 PM on Tuesday October 13, 2020.
## 
## Dataset    :  dabestdat
## X Variable :  x
## Y Variable :  y
## 
## Unpaired mean difference of treatment (n = 50) minus control (n = 50)
##  11.2 [95CI  8.18; 14.6]
## 
## 
## 5000 bootstrap resamples.
## All confidence intervals are bias-corrected and accelerated.

# Produce a Cumming estimation plot.
plot(unpaired_meandiff)