Hi Folks,
I'd be grateful for suggestions about approaching the
following kind of data. I'm not sure what general class of
models it is best situated in (that's just my ignorance),
and in particular if anyone could point me to case studies
associated with an R approach that would be most useful.
Suppose I have data of the following kind. Each "subject"
is observed at say 4 time-points T2, T2, T3, T4, yielding
values of binary (0/1) variables X1, X2, X3, X4. At time T4
is also observed a binary variable Y. The objective is to
study the predictive power of (X1, X2, X3, X4) for the
outcome "Y=1".
A useful model should take account of the possibility
that more "recent" X's are likely to be better predictors
than less "recent" so that, say, P(Y=1|X4=1) is likely to
be larger than P(Y=1|X1=1), and also that the more X's
are 1, the more likely it is that Y=1.
Any suggestions or comments and, as I say, pointers to
an R treatment of similar problems would be most welcome.
With thanks,
Ted.
--------------------------------------------------------------------
E-Mail: (Ted Harding) <Ted.Harding at manchester.ac.uk>
Fax-to-email: +44 (0)870 094 0861
Date: 11-Mar-08 Time: 00:17:14
------------------------------ XFMail ------------------------------
