# [R] MDS with ranking data (and transformation)

Charles C. Berry cberry at tajo.ucsd.edu
Sun Feb 15 20:24:49 CET 2009

```On Sun, 15 Feb 2009, achristoffersen wrote:

>
> Dear Sirs and madams :-)
>
> I am trying to teach myself multidimensional scaling. To that effect I have
> collected a survey asking people to rank 10 philosophers and politicians
> according to their preference. I have collected 61 answers. The data is
> organized in ten columns and 61 rows. the columns are "choice_1",
> "choice_2", "choice_3" etc. The cells is the name of the philosopher
>
> I guess I need to put the data in some other format, e.g. with colloumns:
> "philospher_1", "philospher_2", "philospher_3" etc. and then have the cell
> hold the particular ranking (score) for that philospher (i.e. a number
> between 1:10)
>
> I guess such a transformation would also allow me to do clusteranalysis? -
> But how to do it???

Something like

dat <- t( apply( your.data, 1 , order ) )
colnames(dat) <- paste( 'philosopher', 1:10, sep='_' )

HTH,

Chuck

>
> Anyways: what I have done so far is to compute a 10*10 matrix in a
> spreadsheet application. I do this by
> countif(range_choice1=philospher1)*10 for each philospher.
> In “range_choice2” I multiply by 9, and in “range_choice3” I multiply with 8
> etc.
>
> The corresponding matrix I import to r and do
> dist(t(matrix)
> and then I use cmdscale\$points to draw a plot. It looks nice but I am almost
> sure I'm doing it wrong. And I would certainly like not having rely on a
>
> So my question is: how to transform the data, and is it true that my current
> 'spreadsheet' method is wrong? Also: should consider discarting some data,
> e.g. only using the top 3 choices?
>
>
> Andreas
> --
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