install.packages('bmem')
library(bmem)

### Step 1. Prepare data  ###
# Read data into R and store them in an object called dset
dset<-read.table("rdata.txt", header=T)

### Step 2. Specify the model  ###
M1<-specifyEquations(exog.variances=T)
  math = b*HE + c*ME
  HE = a*ME
   
### Step 3. Run the analysis  ###
indirect<-c('a*b', 'a*b+c')
M1.res<-bmem(dset, M1, indirect, boot=1000, method='mi', m=100)

### plot the bootstrap distribution
plot(M1.res, 'a*b')
plot(M1.res, 'a*b+c')