[R] impute missing values in correlated variables: transcan?

[Jonathan Baron]

On 11/30/04 11:23, roger koenker wrote:
>At the risk of stirring up a hornet's nest , I'd suggest that
>means are dangerous in such applications.  A nice paper
>on combining ratings is:  Gilbert Bassett and Joseph  Persky,
>Rating Skating,  JASA, 1994,  1075-1079.

Here is the abstract, which seems to capture what the article
says:

"Among judged sports, figure skating uses a unique method of
median ranks for determining placement. This system responds
positively to increased marks by each judge and follows majority
rule when a majority of judges agree on a skater's rank. It is
demonstrated that this is the only aggregation system possessing
these two properties. Median ranks provide strong safeguards
against manipulation by a minority of judges. These positive
features do not require the sacrifice of efficiency in
controlling measurement error. In a Monte Carlo study, the median
rank system consistently outperforms alternatives when judges'
marks are significantly skewed toward an upper limit."

I think this is irrelevant.  We are using ratings, not rankings.

(And there was a small error in my original post.  The disturbing
effect of missing data at the high or low end would be on the
slope rather than the intercept or mean.)

Jon
-- 
Jonathan Baron, Professor of Psychology, University of Pennsylvania
Home page: http://www.sas.upenn.edu/~baron