Even then, I think that there's a problem. If C is in the model, then the response varies by C. The simplest way is to pick a value for C, and then evaluate the group mean estimates of A and B (and C).
Something in my brain keeps asking whether another way to marginalize C for the purposes of predicting A and B is just to remove it from the model, or alternatively to make it a random effect. Neither idea seems rock solid at this point. Cheers Andrew On Thu, May 05, 2011 at 09:37:15AM -0400, Pang Du wrote: > Oops, I hope not too. Don't know why I had the brackets around B+C. My > model is actually A*B+C. And I'm not sure how to obtain the two-way > prediction of AB with C marginalized. Thanks. > > Pang > > -----Original Message----- > From: Andrew Robinson [mailto:a.robin...@ms.unimelb.edu.au] > Sent: Wednesday, May 04, 2011 10:13 PM > To: Pang Du > Cc: r-help@r-project.org > Subject: Re: [R] two-way group mean prediction in survreg with three factors > > I hope not! > > Facetiousness aside, the model that you have fit contains C, and, > indeed, an interaction between A and C. So, the effect of A upon the > response variable depends on the level of C. The summary you want > must marginalize C somehow, probably by a weighted or unweighted > average across its levels. What does that summary really mean? Can > you meaningfully average across the levels of a predictor that is > included in the model as a main and an interaction term? > > Best wishes > > Andrew > > On Wed, May 04, 2011 at 12:24:50PM -0400, Pang Du wrote: > > I'm fitting a regression model for censored data with three categorical > > predictors, say A, B, C. My final model based on the survreg function is > > > > Surv(..) ~ A*(B+C). > > > > I know the three-way group mean estimates can be computed using the > predict > > function. But is there any way to obtain two-way group mean estimates, say > > estimated group mean for (A1, B1)-group? The sample group means don't > > incorporate censoring and thus may not be appropriate here. > > > > > > > > Pang Du > > > > Virginia Tech > > > > > > [[alternative HTML version deleted]] > > > > ______________________________________________ > > R-help@r-project.org mailing list > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > > and provide commented, minimal, self-contained, reproducible code. > > -- > Andrew Robinson > Program Manager, ACERA > Department of Mathematics and Statistics Tel: +61-3-8344-6410 > University of Melbourne, VIC 3010 Australia (prefer email) > http://www.ms.unimelb.edu.au/~andrewpr Fax: +61-3-8344-4599 > http://www.acera.unimelb.edu.au/ > > Forest Analytics with R (Springer, 2011) > http://www.ms.unimelb.edu.au/FAwR/ > Introduction to Scientific Programming and Simulation using R (CRC, 2009): > http://www.ms.unimelb.edu.au/spuRs/ -- Andrew Robinson Program Manager, ACERA Department of Mathematics and Statistics Tel: +61-3-8344-6410 University of Melbourne, VIC 3010 Australia (prefer email) http://www.ms.unimelb.edu.au/~andrewpr Fax: +61-3-8344-4599 http://www.acera.unimelb.edu.au/ Forest Analytics with R (Springer, 2011) http://www.ms.unimelb.edu.au/FAwR/ Introduction to Scientific Programming and Simulation using R (CRC, 2009): http://www.ms.unimelb.edu.au/spuRs/ ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
