[R] individual scales in random subset of pairwise distance survey

[Gabor Grothendieck]

The diag(1,n) was not needed:


set.seed(1)
n <- 25
mat <- matrix(0, n, n)
rownames(mat) <- colnames(mat) <- letters[1:n]
mat[lower.tri(mat)] <- sample(5, n * (n-1)/2, TRUE)
mat <- mat + t(mat)
plot(hclust(as.dist(mat)))


On 6/15/06, Gabor Grothendieck <ggrothendieck at gmail.com> wrote:
> Perhaps you could try clustering the objects.
>
> # generate test data
> set.seed(1)
> n <- 25 # number of items
> mat <- matrix(0, n, n)
> # use different labelling scheme if > 26 items
> rownames(mat) <- colnames(mat) <- letters[1:n]
> mat[lower.tri(mat)] <- sample(5, n * (n-1)/2, TRUE)
> mat <- mat + t(mat) + diag(1, n)
>
> # cluster and plot
> plot(hclust(as.dist(mat)))
>
>
> On 6/15/06, context grey <mobygeek at yahoo.com> wrote:
> >
> > Hello,
> >
> > I'm curious if anyone has encounted a version of this
> > problem
> > (and it's solution) involving finding a consistent set
> > of scales
> > for subsets of survey data.
> >
> > The goal is to obtain peoples' rankings of pairwise
> > similarity of a large
> > number of items, on a 1..5 scale for example, and
> > average these
> > across people to use as input to MDS:
> >  How similar is object A to B    on a 1..5 scale ___
> >  How similar is object A to C    on a 1..5 scale ___
> > etc.
> >
> > Because there are many items, there are N(N-1)/2
> > pairs, so it is not
> > practical to show every pair to everyone.   Showing
> > people the
> > pairs corresponding to random subsets of the objects
> > seems desirable.
> >
> > THe problem is that, a particular random subset might
> > by chance
> > contain objects that would all be rated "5" if one
> > were to see
> > the entire dataset.  When ranking pairs from this
> > subset, the scale
> > of 1..5 is different.
> >
> > If we ensure that each pair of people must see some
> > data in common,
> > then one can think about obtaining a set of scales,
> > one for each
> > person, that causes the data that is commonly ranked
> > to have
> > as similar scores as possible, summed across all pairs
> > of people.
> >
> >
> > Please let me know if you know of a standard procedure
> > for
> > this or any similar problems.
> >
> > Thank you.
> >
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>