From: Douglas Bates <dmbates_at_gmail.com>

Date: Sat 24 Sep 2005 - 00:00:26 EST

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 Received on Sat Sep 24 00:11:44 2005

Date: Sat 24 Sep 2005 - 00:00:26 EST

On 9/20/05, Felipe <felipe@unileon.es> wrote:

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As Deepayan said in his reply, the concept of least squares means is associated with SAS and is not generally part of the theory of linear models in statistics. My vague understanding of these (I too am not a SAS user) is that they are an attempt to estimate the "mean" response for a particular level of a factor in a model in which that factor has a non-ignorable interaction with another factor. There is no clearly acceptable definition of such a thing.

To understand why there should be an attempt to answer a question that doesn't make sense, remember the history of SAS, which was developed in the era of punched cards and magnetic tape. Beneath the surface of SAS with its GUI, etc. is the fundamental assumption that your data are on a reel of magnetic tape over in the "Computer Center" that houses an IBM Sytem/360 computer and that the way you are going to use this program is by keypunching a deck of punched cards, putting some mysterious JCL (the IBM Job Control Language which no one understood and you learned only by imitation) cards at the beginning and end, and submitting them at the I/O Window. The next day you will go to the computer center to pick up your output only to discover that you had a JCL error. You will spend most of the morning tracking down the one person on campus who can tell you that "ERROR IEH92345" was caused by the blank between the "DD" and the "*" in the card that reads //SYSIN DD * so you change that and submit again. After two or three days of this you get the JCL right but discover that you have a syntax error in your SAS code. Another two or three cycles finally gets you to the point where you have a card deck that runs and produces output. At that point you don't really care if the output makes sense or not - all you want is some numbers for the report that is now a week overdue. You also want all the numbers that you might possibly need, which is why SAS PROCs always have the potential to produce tons of output if you ask for it.

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 Received on Sat Sep 24 00:11:44 2005

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