R suitability for development project
Jim wrote:
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.
I note: Thank you for the detailed answer. I have the raw ranks. For a question they look like this; 1=Item2, 2=Item1, 3=Item3, 4=Item4
Jim wrote:
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
I note: Is it possible to have the output as an integer where 99 is the highest score?
Jim wrote:
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.
I note: The look I am aiming to achieve (as shown here: http://community.abeo.us/sample-graphs/ ) is a relative position within the middle zero based horizontal axis. The mean is not required. Since all bars are 14 units long the upper and lower values note where the end of each bar should align, either to the right for Highest or to the left for Lowest. The third graph shows both. ~eric
On Mon, Sep 3, 2012 at 7:41 AM, Jim Lemon <jim at bitwrit.com.au> wrote:
Eric Langley wrote:
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.
Eric Langley Founder eric at abeo.us 404-326-5382