Dear Frank, The object is to focus on a high-order term of the model, holding other terms "constant" at typical values; in the case of a factor, a "typical value" is ambiguous, so an average is taken over the levels of the factor. If the factor is, e.g., gender, one could produce an estimate of the average fitted value for a population composed equally of men and women, or of a population composed of men and women in proportion to their distribution in the data. Otherwise, one would have to produce separate sets of fitted values for men and women, with the number of such sets increasing as the number of levels of the factors held constant increase. On the scale of the linear predictor, these sets would differ only by constants.
Regards, John -------------------------------- John Fox Department of Sociology McMaster University Hamilton, Ontario Canada L8S 4M4 905-525-9140x23604 http://socserv.mcmaster.ca/jfox -------------------------------- > -----Original Message----- > From: Frank E Harrell Jr [mailto:[EMAIL PROTECTED] > Sent: Thursday, March 22, 2007 8:41 AM > To: John Fox > Cc: 'Prof Brian Ripley'; 'r-help'; 'Chuck Cleland'; 'Liaw, Andy' > Subject: Re: [R] how to get "lsmeans"? > > John Fox wrote: > > Dear Brian et al., > > > > My apologies for chiming in late: It's been a busy day. > > > > First some general comments on "least-squares means" and > "effect displays." > ... much good stuff deleted ... > > John - the one thing I didn't get from your post is a > motivation to do all that as opposed to easy-to-explain > predicted values. I would appreciate your thoughts. > > Thanks > Frank > > -- > Frank E Harrell Jr Professor and Chair School of Medicine > Department of Biostatistics > Vanderbilt University ______________________________________________ R-help@stat.math.ethz.ch 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.