accov1<-function(respmat){



## This program calculates the average conditional    ##

## covariance matrix for a 0-1 data set.  BH 1/12/04  ##				



  nitem<-ncol(respmat) 

  nexmn<-nrow(respmat)

  covmat<-matrix(0,nrow=nitem,ncol=nitem)

  score<-apply(respmat,1,sum)



## deal with each item pair one at a time ##



  for (i in 1:(nitem-1)) {

    for (j in (i+1):nitem) {



## construct the strata for the item pair ##



      strata<-array(0,dim=c(2,2,(nitem-1)))

      scoretemp<-score-respmat[,i]-respmat[,j]

      for (k in 1:nexmn){

        strata[respmat[k,i]+1,respmat[k,j]+1,scoretemp[k]+1]<-

          strata[respmat[k,i]+1,respmat[k,j]+1,scoretemp[k]+1]+1

      } 



## calculate the covariance times number of ##

## examinees for each score level           ##



      ntotal<-0

      for (k in 1:(nitem-1)){

        n<-strata[1,1,k]+strata[1,2,k]+strata[2,1,k]+strata[2,2,k]

	p11<-strata[2,2,k]

	p1<-strata[2,1,k]+strata[2,2,k]

        p2<-strata[1,2,k]+strata[2,2,k]

	if (n>1){ 

          ntotal<-ntotal+n 

          covmat[i,j]<-covmat[i,j]+n*(p11/n-(p1/n)*(p2/n))

        }

      }



## divide by the total number of examinees   ##

## and then get the lower half of the matrix ##



      covmat[i,j]<-covmat[i,j]/ntotal

      covmat[j,i]<-covmat[i,j]    



## go on to the next item pair



    }

  }



## return the output and finish ##



  return(covmat)

}



a1291<-read.fwf("http://www.stat.sc.edu/~habing/courses/data/a1291nospace.txt",widths=rep(1,24))



accov2<-function(respmat,include=F){



## This program calculates the average conditional  	##

## covariance matrix for a 0-1 data set.  By F. Vera	##	



 nitem<-ncol(respmat)

 ccov<-matrix(0,nrow=nitem,ncol=nitem)

 score<-apply(respmat,1,sum)

 for (i in 1:(nitem-1)) {

   for (j in (i+1):nitem) {

     scoretemp<-score-respmat[,i]-respmat[,j]+1

     irfi<-tapply(respmat[,i],scoretemp,sum)

     irfj<-tapply(respmat[,j],scoretemp,sum)

     irfij<-tapply(respmat[,i]*respmat[,j],scoretemp,sum)

     numatscore<-table(scoretemp)

     numatscore2<-numatscore[numatscore>1]

     irfi<-irfi[numatscore>1]/numatscore2

     irfj<-irfj[numatscore>1]/numatscore2

     irfij<-irfij[numatscore>1]/numatscore2

     ccov[i,j]<-sum((irfij-irfi*irfj)*numatscore2)/sum(numatscore2)

     ccov[j,i]<-ccov[i,j]

   }

 }

  return(ccov)

}