R/Fcurve.R

In TestGardener: Information Analysis for Test and Rating Scale Data

Fcurve <- function(SfdList, chcevec, nderiv=0) {
  #  FCURVE computes 101 values one of the first three derivatives of the  
  #. negative log likelihood for a set of examinees over [the width of 
  #. the interval [0,100] at 101 equally spaced points..
  #. Arguments:
  #  SfdList   ... A list vector containing descriptions of each item
  #. The curve is defined for each rater by the choices made.
  #  chcevec         ... The N by n matrix of choice indices
  #. nderiv    ... The order of derivative selected from 0, 1 or 2.
  
  #  Last updated 21 November 2023
  
  #. Deal with a single choice vector that is numeric
  if (!is.matrix(chcevec)) chcevec <- t(as.matrix(chcevec))
  nitem <- ncol(chcevec)
  
  #  loop through items to compute negative log likelihood values in F
  
  Ffine <- matrix(0,101,1)
  for (item in 1:nitem) {
    # print(item)
    chceij <- chcevec[1,item]
    if (!(is.null(chceij))) {
      SListi <- SfdList[[item]]
      Smati  <- SListi$Smatfine
      if (chceij <= ncol(Smati)) {
        if (nderiv == 0) {
          Ffine <- Ffine + Smati[,chceij]
        }
        if (nderiv == 1) {
          DSmati <- SListi$DSmatfine
          Ffine  <- Ffine + DSmati[,chceij]
        }
        if (nderiv == 2) {
          D2Smati <- SListi$D2Smatfine
          Ffine   <- Ffine + D2Smati[,chceij]
        }
      }
    }
  }
  
  return(Ffine)
  
}