Eric Langley wrote:
Hello All,
Eric Langley here with my first post to this list. I am looking to
determine if R is suitable for a development project I am working on
and if so possibly finding someone proficient in R that would be
interested in doing the coding.
I would like to preface my inquiry that while I am not a programmer I
can communicate in a dialog my objectives.
An array of rank ordered data looks like this:
Item-Rank First Second Third Fourth Totals
Item1 6 8 0 0 14
Item2 7 5 2 0 14
Item3 1 1 11 1 14
Item4 0 0 1 13 14
Totals 14 14 14 14
The required output of R will be two fold;
1, a numerical score for each of the Items (1-4) from highest to
lowest and lowest to highest on a scale of 0-99 that is statistically
accurate. For this example the scores would be Item1 highest number
down to Item4 with the lowest number. In reverse Item4 would be the
highest number down to Item1 the lowest number. For the Highest like
this; Item1=94, Item2=88, Item3=48, Item4=2 (just guessing here on the
scores...:)
2, a graphical output of the data based on the scores in three special
graphs with a middle line at '0' and increasing numbers to the left
AND right. The graphs plot the Highest ranked Items, the Lowest Ranked
items and a combination of the two.
Sample graphs are here: http://community.abeo.us/sample-graphs/
Looking forward to hearing if R will be able to accomplish this.
Hi Eric,
I would use mean ranks for something like this. You would have to
calculate these from your summary array unless you have the raw ranks.
ranksumm2meanranks<-function(x,nobs) {
nitems<-dim(x)[1] - 1
meanrankvec<-rep(0,nitems)
for(rankrow in 1:nitems) {
for(rankcol in 1:nitems)
meanrankvec[rankrow]<-
meanrankvec[rankrow]+x[rankrow,rankcol]*rankcol
meanrankvec[rankrow]<-
meanrankvec[rankrow]/x[rankrow,nitems+1]
}
names(meanrankvec)<-rownames(x)[-1]
return(meanrankvec)
}
> ranksumm2meanranks(x)
Item2 Item3 Item4 Totals
1.571429 1.642857 2.857143 3.928571
You can obtain the "reversed" ranks by subtracting the above from the
maximum rank score (4), but I don't see why you would want to do this.
Your explanation of the plot is not entirely clear. The ranges of the
ranks for the items are:
Item1 c(1,2)
Item2 c(1,3)
Item3 c(1,4)
Item4 c(3,4)
You could plot these as horizontal bars spanning the range of the ranks
for each item with a vertical line across each bar showing the value of
the mean rank for that item. This would illustrate both the relative
position and variability of ranks, something like a boxplot.
In case you have incomplete ranks, check the crank package for
completion of incomplete ranks.
Jim
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