[R] Item Analysis and Cronbach's Alpha (Code Attached)

[Magill, Brett]

A short function I wrote for the purpose of evaluating scales made up of a
number of questionnaire items.  It provides Cronbach's Alpha, both
unstandardized and based on standardized items.  It also provides item
statistics which include item-total correlations (corrected) and
item-removed alpha.  Thought some of you might find it useful.  I would also
appreciate any programming tips or suggestions for improving the function as
I am still relatively new to R and statistical programming in general.

Cheers!


Alpha<-
function(x){
  xmat<-as.matrix(na.omit(x))
  xmat.z<-scale(xmat)
  N<-dim(xmat)[2]
  Correlation.Matrix<-cor(xmat)

  Item.Tot.Cor<-rep(NA,N)
  for (a in 1:N) Item.Tot.Cor[a]<-(cor(apply(xmat[,- a],1,sum),xmat[,a]))

  Item.Rem.Alpha<-rep(NA,N)
  for (b in 1:N) Item.Rem.Alpha[b]<- ((N-1)/(N-2)) * (1
-((sum(diag(var(xmat[,-b])))) / (sum(var(xmat[,-b])))))

  Item.Mean<-apply(xmat,2,mean)
  Item.SD<-apply(xmat,2,sd)
  Item.Var<-apply(xmat,2,var)
  N.Cases<-rep(dim(xmat)[1],N)
  ITEM.STATISTICS<-cbind(Item.Mean, Item.Var,
Item.SD,Item.Tot.Cor,Item.Rem.Alpha,N.Cases)

  Cronbachs.Alpha<-   (N/(N-1)) * (1 -((sum(diag(var(xmat  )))) /
(sum(var(xmat  )))))
  Standardized.Alpha<- (N/(N-1)) * (1 -((sum(diag(var(xmat.z)))) /
(sum(var(xmat.z)))))
  Total.Mean<-mean(apply(xmat,1,sum))
  Total.Var<-var(apply(xmat,1,sum))
  Total.SD<-sd(apply(xmat,1,sum))
  N.Items<-N
 
TOTAL.STATISTICS<-cbind(Cronbachs.Alpha,Standardized.Alpha,Total.Mean,Total.
Var,Total.SD, N.Items)
  row.names(TOTAL.STATISTICS)<-"TOTAL"
  print("Cronbach's Alpha and Item Analysis")
  print("----------------------------------")
  print("Correlation.Matrix")
  print(Correlation.Matrix,digits=4)
  print("---------------------------------------------------------")
  print(ITEM.STATISTICS,digits=4)
 
print("------------------------------------------------------------------")
  print(TOTAL.STATISTICS,digits=4)
}
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