LISTSERV at the University of Georgia
Menubar Imagemap
Home Browse Manage Request Manuals Register
Previous messageNext messagePrevious in topicNext in topicPrevious by same authorNext by same authorPrevious page (November 1996)Back to main SPSSX-L pageJoin or leave SPSSX-L (or change settings)ReplyPost a new messageSearchProportional fontNon-proportional font
Date:   Mon, 4 Nov 1996 10:19:59 -0500
Reply-To:   "William B. Ware" <wbware@EMAIL.UNC.EDU>
Sender:   "SPSSX(r) Discussion" <SPSSX-L@UGA.CC.UGA.EDU>
From:   "William B. Ware" <wbware@EMAIL.UNC.EDU>
Subject:   Re: Simple mixed design
Comments:   To: Jennifer Marshall <stat010@BOISDARC.TAMU-COMMERCE.EDU>
In-Reply-To:   <96Nov4.091442-0500_est.15775-149496+180@email.unc.edu>

On Mon, 4 Nov 1996, Jennifer Marshall wrote:

> I am doing a simple mixed design with one between subjects factor and one > within subjects factor.I have gotten an error term for the between > subjects factor and for the interaction of the within and between subject > factors. I do not understand where the error term comes from. > Could someone please explain the error term AND where it comes from?

Here is the way that I conceptualize the design, as I understand you. Let's call the between-factor A and the within-factor B. You have observations nested within the A factor, but crossed with the B factor. You should have two error terms: a between and a within. The "between" error term is simply the pooled error term within each level of A. That is, there are cases within A1, cases within A2, etc. It works just like a oneway design. The "within" error term serves for both the B effect and the A*B effect.

Think of the "within" term this way. Within each level of A, you have a randomized block design; cases by B. Within each of those designs, you have a B effect, a subjects effect, and a residual. The overall "within subjects" error term is the pooled residuals...

In testing B and A*B, you need to attend to some assumptions. First, that you have homogeneity of residuals, and that the pooled variance-covariance matrix is "symmetric." You might want to look at Roger Kirk's book on Experimental Design.

______________________________________________________________________________

William B. Ware, Professor and Chair Educational Psychology CB# 3500 EMAIL: wbware@unc.edu University of North Carolina PHONE: (919)-966-5266 Chapel Hill, NC 27599-3500 FAX: (919)-962-1533

URL:http://www.unc.edu/~wbware/ ______________________________________________________________________________


Back to: Top of message | Previous page | Main SPSSX-L page