```Date: Mon, 12 Dec 2005 10:01:39 -0600 Reply-To: "Swank, Paul R" Sender: "SPSSX(r) Discussion" From: "Swank, Paul R" Subject: Re: mixed design repeated measures question Comments: To: ZEYNEP CEMALCILAR Content-Type: text/plain; charset="us-ascii" What it means is that the difference between the pre- and posttests for the control and treatment groups is not the same for the two levels of SES. You could do simple main effects because it is possible for the differences to be significant in both cases but to be larger at one level that the other. However, I usually just graph the results. With 1 df for the test, all independnet hypotheses are already tested. Simple man ewffects do represent confounded effects. Paul R. Swank, Ph.D. Professor, Developmental Pediatrics Director of Research, Center for Improving the Readiness of Children for Learning and Education (C.I.R.C.L.E.) Medical School UT Health Science Center at Houston -----Original Message----- From: SPSSX(r) Discussion [mailto:SPSSX-L@LISTSERV.UGA.EDU] On Behalf Of ZEYNEP CEMALCILAR Sent: Monday, December 12, 2005 12:58 AM To: SPSSX-L@LISTSERV.UGA.EDU Subject: mixed design repeated measures question I'd like to ask your help in interpreting findings on a mixed-design repeated measures test. In my design I have one within factor (pre-post test scores- I named this factor as Time) and 2 between factors (ses and treatment group). My analysis gives a significant interaction of all these three factors such that: Interaction of Time, SES, and Treatment is F (1,229) = 6,505 p=,011. As far as I understand this means: The intervention's effect for each treatment group (exp vs control) is dependent on the SES (hi-low). How do I conduct further analysis to understand where the difference exactly comes from? Graphs show that my treatment has a differential effect between my low- hgh ses groups. What is the part of the analysis I need to look at for this effect? (contrast subcommand only gives me the main effects for treatment and ses) Is it accceptable to split the whole sample by SES and Treatment and do a paired t-test where I compare the average post-pre scores of experimental / control groups in each SES group? Thanks Z- ```

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