R/hartzRoussosQ.R

In drackham/dcmdata: Diagnostic Classification Model Data Simulations

#' Hartz Roussos (2008) Q-matrix
#'
#' Simulates the Hartz Roussos Q-matrix from "The Fusion Model for Skills Diagnosis: Blending Theory with Practicality" (2008)
#'
#' @author Dave Rackham \email{ddrackham@gmail.com}
#' @references \url{http://onlinelibrary.wiley.com/doi/10.1002/j.2333-8504.2008.tb02157.x/abstract}
#' @keywords q-matrix hartz roussos
#'
#' @examples
#' q <- hartzRoussosQLow()
#'
#' @export

hartzRoussosQLow <- function(){
  q <- matrix (nrow=40, ncol=7) #Column 3 is evidence models
  #           1 2 3 4 5 6 7
  q[1,]  <- c(0,0,1,0,1,0,0)
  q[2,]  <- c(1,0,0,0,0,0,0)
  q[3,]  <- c(1,0,0,0,1,0,0)
  q[4,]  <- c(0,0,0,0,0,0,1)
  q[5,]  <- c(1,0,0,1,0,0,0)
  q[6,]  <- c(0,1,0,0,1,0,1)
  q[7,]  <- c(0,0,1,1,0,0,1)
  q[8,]  <- c(0,0,1,0,1,0,0)
  q[9,]  <- c(0,0,1,0,1,0,0)
  q[10,] <- c(0,0,0,1,0,0,0)

  #           1 2 3 4 5 6 7
  q[11,] <- c(0,0,0,0,0,1,0)
  q[12,] <- c(0,0,0,0,0,0,1)
  q[13,] <- c(1,0,0,1,0,0,1)
  q[14,] <- c(0,0,0,1,0,0,0)
  q[15,] <- c(0,1,1,0,0,0,0)
  q[16,] <- c(0,0,0,0,1,0,1)
  q[17,] <- c(0,0,0,0,1,0,1)
  q[18,] <- c(1,0,1,0,0,1,1)
  q[19,] <- c(1,0,0,0,0,1,0)
  q[20,] <- c(1,0,0,0,0,0,0)

  #           1 2 3 4 5 6 7
  q[21,] <- c(0,1,0,0,0,0,0)
  q[22,] <- c(0,0,0,0,0,1,0)
  q[23,] <- c(0,0,0,1,0,0,0)
  q[24,] <- c(0,0,0,1,0,1,0)
  q[25,] <- c(0,1,0,0,0,1,0)
  q[26,] <- c(0,0,0,0,1,0,0)
  q[27,] <- c(0,0,0,0,0,1,1)
  q[28,] <- c(0,1,1,1,0,0,0)
  q[29,] <- c(0,1,1,0,1,0,1)
  q[30,] <- c(0,0,1,0,0,0,1)

  #           1 2 3 4 5 6 7
  q[31,] <- c(1,0,0,1,0,1,0)
  q[32,] <- c(0,1,0,1,0,0,0)
  q[33,] <- c(0,0,0,1,0,0,0)
  q[34,] <- c(0,1,1,0,0,1,0)
  q[35,] <- c(1,1,1,0,0,0,0)
  q[36,] <- c(0,1,0,0,1,0,0)
  q[37,] <- c(1,0,0,1,0,0,0)
  q[38,] <- c(0,0,0,0,1,1,0)
  q[39,] <- c(1,0,0,0,0,1,1)
  q[40,] <- c(0,0,0,0,0,1,1)

  return(q)
}