```Date: Thu, 14 Dec 2006 14:15:34 -0500 Reply-To: Statisticsdoc Sender: "SPSSX(r) Discussion" From: Statisticsdoc Subject: Re: Statistical methods to investigate interactions between factors and continuous covariates Comments: To: "Kersting, Nicole" In-Reply-To: <88BF7B0D0A9DF445AD4E8149A2E885EC1FB8A2@USOLDTMS008.PCROOT.COM> Content-Type: text/plain; charset="US-ASCII" Stephen Brand www.statisticsdoc.com Hi Nicole, One of the core assumptions of ANCOVA is that the relationship between the covariate and the dependent variable is the same for both groups. When you have a significant group by covariate interaction, then this assumption is not met. The significant interaction term implies that the relationship between the covariate and the dependent variable differs between groups. As a result, I would not use ANCOVA to analyse these data. I would use a regression framework instead, with the following predictors: 1.) the continuous variable; 2.) dummy codes for the categorical variable (or effect codes, if these are appropriate); 3.) the cross-product, or interaction, between the continuous variable and each of the dummy codes. You can use the regression weights to compute values of the dependent variable for each group at one standard deviation above and below the mean on the continuous variable. These points will allow you to plot the slope and intercept of the continuous variable for each group. HTH, Stephen Brand For personalized and professional consultation in statistics and research design, visit www.statisticsdoc.com -----Original Message----- From: SPSSX(r) Discussion [mailto:SPSSX-L@LISTSERV.UGA.EDU]On Behalf Of Kersting, Nicole Sent: Thursday, December 14, 2006 1:48 PM To: SPSSX-L@LISTSERV.UGA.EDU Subject: Re: Statistical methods to investigate interactions between factors and continuous covariates Hi all, I ran an ANCOVA model which yielded a significant interaction between a fixed factor and a continuous covariate. I am interested in investigating the interaction further but I ran into the following problem: I created a median split in the continuous covariate, which in combination with the factor gave me four means for pairwise comparisons. While I realize all the issues attached to median splits, I have the additional problem that the pairwise comparisons weren;t significant, indicating that the interactions is not represented well by the median split. So I am wondering if there are any other statistical methods to investigate an interaction between a continuous covariate and a factor or if I am doomed to fish around for the appropriate split because for reporting purposes I will need the pairwise comparisons. What do people do in general in those cases. Given that we didn't expect the interaction (not part of the design) it's hard to come up with a theoretical rationale on how to split the data for pairwise comparisons and graphs. Many thanks in advance, Nicki *********************************************************************** This email may contain confidential material. If you were not an intended recipient, please notify the sender and delete all copies. We may monitor email to and from our network. *********************************************************************** ```

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