logit_logLik <- function(dummy,fitted_values){
   # Description: Computes log-likelihood of a fitted
   # logit model

   # Format variables
   y <- as.matrix(dummy)
   p <- as.matrix(fitted_values)
   # Adjust dimensions
   skip <- dim(y)[1] - dim(p)[1]
   y    <- as.matrix(y[-c(1:skip),])

   # Compute log-likelihood
   item <- sapply(1:dim(y)[1], function(i)
                          y[i,]*log(p[i,]) + (1-y[i,])*log(1-p[i,]))
   return(sum(item))
 }