Dear Mike,
Thanks for your helpful information. I also thank Jim Clark for looking at at
printout.
The distinction seems to hinge on whether weighting is taken into account.
Sincerely,
Stuart
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"Recti cultus pectora roborant"
Stuart J. McKelvie, Ph.D., Phone: 819 822 9600 x 2402
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From: Michael Palij [[email protected]]
Sent: 14 December 2011 19:17
To: Teaching in the Psychological Sciences (TIPS)
Cc: Michael Palij
Subject: Re: [tips] SPSS Question for Statistical Tipsters
I have not seen an SPSS source on this point but there are a few discussions
about it by SAS users. One source is the following:
http://support.sas.com/onlinedoc/913/getDoc/en/statug.hlp/glm_sect34.htm
What SAS calls "LS means" or "Least Squares means" is equivalent to SPSS'
estimated marginal means (emm). Ordinary means are referred to as "arithmetic
means";
see the following for the distinction:
http://onbiostatistics.blogspot.com/2009/04/least-squares-means-marginal-means-vs.html
If you have a "balanced" design (e.g., a factorial design with constant N for
each cell),
then the LS/emm means will be the same as the arithmetic means. In an
unbalanced
design, the type of sums of square calculation you use can produce differences
between
the two (e.g., Type I SS or sequential SS vs.Type III SS or unweighted means).
See the following for a worked example:
http://www.public.iastate.edu/~dnett/S402/wlsmeans.pdf
-Mike Palij
New York University
[email protected]<mailto:[email protected]>
------------------- Original Message ------------------------
On Wed, 14 Dec 2011 12:09:11 -0800, Jim Clark wrote:
Hi
I have not observed this problem and, as Stuart observed, generally see
EMMs that differ from originals when covariates are involved. One thing
to check might be whether it occurs with unequal ns per condition /
cell? Could SPSS be estimating effects controlling for any confounding
between factors?
If you have an example of this issue, I would be happy to see it.
Take care
Jim
>>> Stuart McKelvie <[email protected]<mailto:[email protected]>>
>>> 14-Dec-11 12:38 PM >>>
Dear Tipsters,
I have puzzled over this question for a long time.
When conducting an ANOPVA in SPSS, we have two options for obtaining
means in each condition.
1. Click on descriptives. This gives means, standard deviations and
sample sizes for all main effects and interactions. They appear at the
beginning of the printout.
2. Under options, you can specify which means you want. This gives
means and standard errors for the effects and interactions that you
specify. They appear at the end of the printout.
My question is: Why are these means sometimes different from the ones
in the descriptives in 1? I think I have seen the term "estimated
marginal means", with a reference to covariates, but if there are no
covariates (it is ANOVA not ANCOVA), I do not understand this.
I would have thought that a mean was a mean in ANOVA.
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