Ista There are several functions in the MiscPsycho package that can be sued for classical item analysis.
> -----Original Message----- > From: r-help-boun...@r-project.org > [mailto:r-help-boun...@r-project.org] On Behalf Of Ista Zahn > Sent: Tuesday, March 10, 2009 10:28 AM > To: reve...@northwestern.edu > Cc: r-help@r-project.org > Subject: [R] reliability, scale scores in the psych package > > Dear Professor Revelle and R-helpers, > This is a two-part question: the first part is general, and > the second is specific to the psych package. > > First question: In the past I've constructed composite > variables from questionnaire data by using rowMeans(), and > then correlating items with the scale using cor() as an > informal check for "bad" items. Over the weekend I decided to > take a look at some of the packages in the psychometric task > view, to see if there was a way to simplify this process. I > looked at several packages, including psychometric, CTT, and > psych. I'm interested in hearing from others who need to do > this kind of thing frequently. What approach do you use? Do > you use one of the packages mentioned above? Are there other > packages I might want to take a look at? > > Second question: I spent some time with the psych package > trying to figure out how to use the score.items() function, > and it's become clear to me that I don't understand what it's > doing. I assumed that setting a key equal to -1 would result > in the item being reverse scored, but I get weird results, as > shown below. When I try to reverse score (by setting a value > of -1 in the key), I get scale scores that don't add up > (e.g., the mean score is reported as being larger than the > maximum item score). How is the score.items() function > intended to be used? Do I need to reverse score items before > using score.items()? > > Thanks, > Ista > > ########## score.items() example begins here ########## > > library(psych) > > Data.score <- > > > as.data.frame(matrix(c(40,29,40,32,1,1,3,1,5,3,3,44,24,47,31,4,4,1,1,4 > > > ,2,1,13,5,14,5,5,4,3,3,4,4,3,7,2,2,0,5,4,2,2,4,4,4,7,6,5,4,1,1,3,4,3,2 > > > ,1,18,15,21,8,6,6,1,1,6,6,6,9,10,15,7,5,4,2,1,5,5,5,10,7,12,6,2,2,4,4, > > 3,3,3,8,7,13,8,1,1,4,2,2,2,1,10,5,13,7,4,3,3,3,3,3,3), nrow=10, > > byrow=TRUE)) > > names(Data.score) <- > > > c("s1","s2","s3","s4","imi1","imi2","imi3","imi4","imi5","imi6","imi7" > > ) > > Data.score > s1 s2 s3 s4 imi1 imi2 imi3 imi4 imi5 imi6 imi7 > 1 40 29 40 32 1 1 3 1 5 3 3 > 2 44 24 47 31 4 4 1 1 4 2 1 > 3 13 5 14 5 5 4 3 3 4 4 3 > 4 7 2 2 0 5 4 2 2 4 4 4 > 5 7 6 5 4 1 1 3 4 3 2 1 > 6 18 15 21 8 6 6 1 1 6 6 6 > 7 9 10 15 7 5 4 2 1 5 5 5 > 8 10 7 12 6 2 2 4 4 3 3 3 > 9 8 7 13 8 1 1 4 2 2 2 1 > 10 10 5 13 7 4 3 3 3 3 3 3 > > > > #This works fine > > key.list <- list(silence=1:4, interest=5:11) keys <- > > make.keys(length(names(Data.score)), key.list, > > item.labels=names(Data.score)) scored <- score.items(keys, > Data.score, > > missing=FALSE, totals=FALSE) scored$scores > silence interest > [1,] 35.25 2.428571 > [2,] 36.50 2.428571 > [3,] 9.25 3.714286 > [4,] 2.75 3.571429 > [5,] 5.50 2.142857 > [6,] 15.50 4.571429 > [7,] 10.25 3.857143 > [8,] 8.75 3.000000 > [9,] 9.00 1.857143 > [10,] 8.75 3.142857 > > > > #This does not do what I expected. Mean interest scores are > higher than score of the highest item. > > key.list2 <- list(silence=1:4, interest=c(5,6,-7,-8,9,10,11)) > > keys2 <- make.keys(length(names(Data.score)), key.list2, > > item.labels=names(Data.score)) > > scored2 <- score.items(keys2, Data.score, missing=FALSE, > totals=FALSE) > > scored2$scores > silence interest > [1,] 35.25 14.71429 > [2,] 36.50 15.28571 > [3,] 9.25 15.42857 > [4,] 2.75 15.85714 > [5,] 5.50 13.57143 > [6,] 15.50 17.42857 > [7,] 10.25 16.42857 > [8,] 8.75 14.14286 > [9,] 9.00 13.57143 > [10,] 8.75 14.85714 > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
