# 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{[email protected]}
#' @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)
}
```
drackham/dcmdata documentation built on May 15, 2019, 1:52 p.m.