R/md_bayes_table.R

In lorenc5/eiCompare: Compares EI, Goodman, RxC Estimates

md_bayes_table <- function(md_results){
  
  if ( paste(names (md_results), collapse="") == paste(c("table", "draws"), collapse="") ) {
    
    md_results <- md_results$table
    
  }
  # Create various iterator/indexing objects #
  len <- nrow(md_results[[1]])
  rnames <- row.names(md_results[[1]])
  num_groups <- length(md_results)
  group_names <- names(md_results)
  
  seq_split <- 2:len
  
  # For tables with just one candidate (somehow) #
  if (len == 1) { 
    
    rn <- c(rnames , "se", "Total")
    
  } else { # More than one candidate #
    
    rn <- c(R.utils::insert(rnames , 
                            ats = seq_split, 
                            values = rep("se", len - 1)), 
            "se", "Total")
  }
  
  # Result NA matrix Holder #
  result_mat <- matrix(NA, ncol=num_groups, nrow=(len*2)+1)
  
  for (j in 1:num_groups) { #open up j loop
    
    n <- len*2
    fill <- rep(NA, n)
    
    odd <- seq(1,n,2) # odd
    even <- seq(2,n,2) # odd
    
    fill[odd] <- md_results[[j]][,1]
    fill[even] <- md_results[[j]][,2]
    
    result_mat[,j] <- c(fill, sum(fill[odd]))
    
  } # close j loop
  
  # Label Columns #
  colnames(result_mat) <- paste("RxC",group_names, sep="_")
  
  # Combine into Dataframe for ei_rc_good_table() function #
  result_mat <- data.frame(Candidate=rn, result_mat, stringsAsFactors = F)
  
  return(result_mat)
  
}