On Wed, 15 Mar 2000 22:48:01 GMT, "JP" <R E M O V E [EMAIL PROTECTED]> wrote: ... > I am in the process of analyzing data of such type: > We have data on 1800 doctors over 49 months:few dependent variables (a > particular drug prescription level), few independent (some time related > (severity of patients seen in the months, practice volume,...) and some > constant over time: university, sex, and years of practive (which can also > be considered as time dependant)). > > id month y timeind1 ... timedep1 ... > 1 1 4 1 30 > 1 2 6 1 36 < snip, lines of eample > > Basically, a bulletin was introduced at month 37, we want to assess if this > bulletin had an effect on a particular drug prescription pattern (y). > What we plan to do is to model y in terms of the dependant variables based > on the first 36 months, and then forecast (including a CI) on the last 13 Huh? Possibly, I am being too hostile to time-series analyses, but it looks to me like there ought to be a simpler approach. What do you know already? What do you expect? That is, how much pattern is there in the early 36 months; and, can't that be reduced to an interesting variable or two.... Siimilarly, what patterns do you expect in the 13 months after; and, can't *those* be reduced to a variable or two.... Then, you have just a handful of variables for each doctor, and 1800 doctors. That should give you quite a lot of ability to describe your interesting patterns, and whatever relates them, using various univariate and multivariate tools. IF you really want the time-series analysis, it sounds like you need to bring in someone with experience at it. Also, for your other question, there is http://www.stattransfer.com/lists.html which has information about joining various mailing lists. -- Rich Ulrich, [EMAIL PROTECTED] http://www.pitt.edu/~wpilib/index.html =========================================================================== This list is open to everyone. Occasionally, less thoughtful people send inappropriate messages. Please DO NOT COMPLAIN TO THE POSTMASTER about these messages because the postmaster has no way of controlling them, and excessive complaints will result in termination of the list. For information about this list, including information about the problem of inappropriate messages and information about how to unsubscribe, please see the web page at http://jse.stat.ncsu.edu/ ===========================================================================
