```Date: Thu, 18 Aug 2005 18:01:47 -0500 Reply-To: "Swank, Paul R" Sender: "SPSSX(r) Discussion" From: "Swank, Paul R" Subject: Re: Ancova results interpretation Comments: To: emaguin@acsu.buffalo.edu Content-Type: text/plain; charset="us-ascii" If the regression lines are not parallel, then at some point they will cross. In the vicinity where they cross, there will be no significant difference between the groups. Thus, you must carefully evaluate the results to ensure an accurate interpretation. One way to address the problem to to determine for what values of the covariate do the groups differ. This can be done artificially by centering the covariate at different values and determining if the groups differ. This procedure does take advantage of chance, like post test comparisons and so may need a correction for the probabilities depending on the number of points you investigate. Paul R. Swank, Ph.D. Professor, Developmental Pediatrics Medical School UT Health Science Center at Houston -----Original Message----- From: SPSSX(r) Discussion [mailto:SPSSX-L@LISTSERV.UGA.EDU] On Behalf Of emaguin@acsu.buffalo.edu Sent: Thursday, August 18, 2005 2:59 PM To: SPSSX-L@LISTSERV.UGA.EDU Subject: Ancova results interpretation All, I have a couple of questions about interpreting ancova results. The basic design is one between factor with two levels (group) and pretest score as covariate. I checked the group by covariate interaction and found it to be significant as well as the group main effect. So i have the case where the regression line differs across the two level of group. I'll report that both the main effect and the group by covariate interaction is significant. I have to confess that i can't remember seeing a report where a group by covariate interaction was significant. What else beyond the above statements needs to be said? More generally, what is done after a group by covariate interaction shows up significant. More to the point, I don't see that this alters my conclusion that posttest scores differ by group after controlling for pretest and allowing for different regression slopes. I'd like to show estimated means. I don't seem to be get them in GLM. I'm using the command ../emmeans table(group). Is that correct or am i missing something? I understand that i can hand calculate them from the unstandardized regression coefficients but can GLM do it? Thanks, Gene Maguin ```

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