Date: Thu, 14 Dec 2006 14:15:34 -0500
Reply-To: Statisticsdoc <statisticsdoc@cox.net>
Sender: "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From: Statisticsdoc <statisticsdoc@cox.net>
Subject: Re: Statistical methods to investigate interactions between
factors and continuous covariates
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.
***********************************************************************
