Prior to executing the code, install the negligible package using install.packages(“negligible”)


#access the negligible package 
library(negligible)

#load dataset
library(datasets)
data(ToothGrowth)
head(ToothGrowth)
##    len supp dose
## 1  4.2   VC  0.5
## 2 11.5   VC  0.5
## 3  7.3   VC  0.5
## 4  5.8   VC  0.5
## 5  6.4   VC  0.5
## 6 10.0   VC  0.5
# Let's compare Guinea pig tooth (odontoblast) length across two groups:
# Group 1) Took Vitamin C via Orange Juice
# Group 2) Took Vitamin C via Ascorbic Acid

# IV = supp (Vitamin C Supplement)
# DV = len (Tooth length)

# Negligible Effect Interval: {-3, 3}

#Simple Set up 
#By default uses the Welch on Trimmed Means
neg.twoindmeans(iv=supp,dv=len,
                data=ToothGrowth, 
                eiL=-3,eiU=3)
## ---- Equivalence of Two Independent Groups----
## 
## Test Statistic: 
##  Schuirmann-Yuen Test of the Equivalence of Two Independent Groups 
## 
## **********************
## 
## Levels of the IV: OJ, VC
## Group Means: 20.66333, 16.96333
## Group Trimmed Means: 21.70556, 16.58333
## Group SDs: 6.605561, 8.266029
## Group MADs: 5.48562, 9.26625
## 
## **********************
## 
## Standardized Mean Difference (SMD): 0.6393216 
## 90% CI for SMD: (0.1517905, 1.210112)
## 
## **********************
## 
## Equivalence Interval: Lower = -3 , Upper = 3 
## 
## **********************
## 
## Mean Difference (MD): 5.122222 
## 90% CI for MD: (1.35, 8.807222)
## 95% CI for MD: (0.3390278, 9.355833)
## 
## **********************
## 
## Proportional Distance (PD): 1.707407 
## 95% CI for PD: (0.1130093, 3.118611)
## 
## **********************
## 
## TOST Test Statistics:
## 
## Ho: mu1-mu2>=eiU:
## t = 0.9476839 (df = 33.49113), p = 0.82496
## 
## Ho: mu1-mu2<=eiL:
## t = 3.627 (df = 33.49113), p = 0.00047
## 
## **********************
## 
## NHST Decision:
## The null hypothesis that the difference between the means exceeds the equivalence interval cannot be rejected. A negligible difference in means cannot be concluded. Be sure to interpret the magnitude of the effect size.
## 
## **********************