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Date:         Wed, 1 Jun 2011 08:52:01 -0700
Reply-To:     Bruce Weaver <bruce.weaver@hotmail.com>
Sender:       "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From:         Bruce Weaver <bruce.weaver@hotmail.com>
Subject:      Re: Interpretation of parameters in loglinear models
In-Reply-To:  <1306940917707-4445521.post@n5.nabble.com>
Content-Type: text/plain; charset=us-ascii

I would work out fitted values of Y for various interesting combinations of the interacting variables, and plot them to display visually the nature of the interaction. This is usually much easier than trying to interpret coefficients for product terms. (Although interpretation of those coefficients becomes a lot easier when you're looking at such a plot, I find.)

Abigail wrote: > > Hello, > > I am trouble using the parameter estimates table to interpret the effects > in my loglinear model- > http://spssx-discussion.1045642.n5.nabble.com/file/n4445521/paremeter.estimates.xls > paremeter.estimates.xls > > Previously I have done crosstabs to examine 2-way terms in my models but > now I have one variable which is a continous covariate (forearm) so now I > am looking at the parameter estimates to interpret the terms that include > my covariate: posture*forearm and diam*no.of.sup*forearm. > > I know that SPSS takes the last category in the variable as a baseline and > therefore does not provide parameter estimates for them. Within my > variables there are no clear base-line categories, I really need to get > values for all of the category combinations in order to fully interpret > the terms in the model but I do not know how to work these out. For the > 3-way relationship it is even more difficult because it only provides > parameter estimates for 1 of the 4 combinations. > > Does anyone know how to work out the values that have been set to zero? Or > is there a better way to interpret interaction terms that involve a > covariate? > > Thanks, > > Abigail >

----- -- Bruce Weaver bweaver@lakeheadu.ca http://sites.google.com/a/lakeheadu.ca/bweaver/

"When all else fails, RTFM."

NOTE: My Hotmail account is not monitored regularly. To send me an e-mail, please use the address shown above.

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