Date: Thu, 7 Jan 2010 12:40:34 -0800
Reply-To: Bruce Weaver <email@example.com>
Sender: "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From: Bruce Weaver <firstname.lastname@example.org>
Subject: Re: regression: multiple Y for each X
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Ian Martin-2 wrote:
> Keith & Gene,
> Thanks for your suggestions. For further background, as Keith
> requested, I have 9 communities, with between 12 and 93 respondents
> per community for a total n of 380. A scatterplot of the nutrition
> variable against the continuous predictor does show an apparent
> linear trend, though of course the groups of multiple Ys overlap
> I don't have much experience with hierarchical or nested designs, and
> the approach I've thought about using is one laid out in Sokal &
> Rohlf's "Biometry" 1981, example in Box 14.4, page 480. I guess
> maybe that dates me, but it seemed appropriate to the data. S&R
> advocate -- as I understand it -- taking ANOVA sum of squares
> (community) minus REGRESSION SS to get deviation from linearity SS.
> Then the REGRESSION MS is tested over the deviation from linearity MS.
I don't have the Sokal & Rohlf book either, but like Gene, I guess they are
probably describing an ANCOVA model. (An old edition of Dave Howell's
textbook shows computation of the various sums of squares for an ANCOVA
model that entail subtracting SS_regression(T) and SS_regression(C) from
SS_regression(T,C), for example, with T and C referring to treatment &
covariate, I think.)
For a very accessible introduction to multilevel models, I heartily
recommend "Applied Multilevel Analysis", by Jos Twisk (Cambridge Press). It
includes a chapter that shows how to run the models in the book with various
software packages, including SPSS.
Regarding the number of communities (or level 2 units, more generally),
Snijders & Bosker (1999) suggest as a rough guideline that ANCOVA be used if
N < 10, and a multilevel model be used if N = 10 or more. But they add that
this guideline should be taken "with a large grain of salt".
"When all else fails, RTFM."
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