Thanks Dale.

I'll hunt around and see what I can find.

Nice weather after the rain the past few days, yes?

You are right, I am trying to minimize SSE. The response variable is pretty wonky, so I was using bootstrapping to get an estimate of model fit and the parameter estimates.

I might be able to use a gamma, but a 3 parameter weibull might also work, if nlmixed supports it. I'll have to see.

Thanks for your help.

Andrew

On 6/20/07, Dale McLerran <stringplayer_2@yahoo.com> wrote: > --- Andrew Hill <hill.andrewd@GMAIL.COM> wrote: > > > Thanks Matthew. > > > > I'll have to look at these more closely. I am hoping that I can find > > one that I can just move the model statement to and just use. It > > would > > make my live simpler. > > > > Does proc nlin mixed require one to use a mixed model? > > > > The one I'm currently using is an exponential model. > > > > change = exp(b0 + b1x1 + b2x2 + b3x3 + b4x4 + b5x5). > > > > I don't want to use proc reg because the data are definitely > > non-normal so the assumption that go into that are wrong for this > > data. > > > > Thanks, > > > > Andrew > > > > Andrew, > > From what you have written here, I would recommend the NLMIXED > procedure all the more. The equation that you specified for AIC > in your previous post assumes that the residuals are normally > distributed. But you indicate above that the response is not > normally distributed. Therefore, you should not be using the > form you specified for computing AIC. > > In response to your specific question as to whether the NLMIXED > procedure requires that you fit a mixed model, the answer is a > resounding NO!!! Just search the SAS-L archives for some examples > (most contributed by yours truly) where NLMIXED is employed to model > all manner of likelihood functions. What the NLMIXED procedure > does require is that one specify a distribution. Based on the > specified distribution, NLMIXED computes maximum likelihood (or > approximate ML) estimates of the parameters of the model. > > I can't tell from way over here, but it sounds as though you > minimized an error sum of squares function in NLIN. Specifying > a distributional model can be more difficult. There may not be > a distribution which is exactly appropriate for your data. But > you can probably specify a distribution which models your > response reasonably well. > > Dale > > > --------------------------------------- > Dale McLerran > Fred Hutchinson Cancer Research Center > mailto: dmclerra@NO_SPAMfhcrc.org > Ph: (206) 667-2926 > Fax: (206) 667-5977 > --------------------------------------- > > > > ____________________________________________________________________________________ > Choose the right car based on your needs. Check out Yahoo! Autos new Car Finder tool. > http://autos.yahoo.com/carfinder/ >