R help - Jul 2012 - Testing significance of interaction between group and longitudinal change for part of the age range in a mixed linear model

Hi all,

I've fit a mixed linear model to some longitudinal data. I'm interested
in the differences in patterns of decrease in the dependent variable according
to group status, and my hypothesis particularly predicts a difference between
the groups in trajectory of change at between specific ages. The data shows a
significant interaction between group and the linear and quadratic effects of
age, but I don't know if there is a way to assess this interaction for one
part of the age range, or if I need to be able to do so in order to interpret my
results as bing supportive of my hypothesis.

Thanks for any help/advice!

1. Your post is unacceptable (imho, of course). Read the bottom of
this message (re: "posting guide") and re-post properly.

2. This is not an R-help question. Re-post on r-sig-mixed-models -- or
perhaps on a non-R statistical forum like stats.stackexchange.com, as
this appears to have little to do with R, per se.

-- Bert



On Thu, Jul 26, 2012 at 9:28 AM, Angela Brant
<angela.brant at googlemail.com> wrote:
>
>
> Hi all,
>
> I've fit a mixed linear model to some longitudinal data. I'm
interested in the differences in patterns of decrease in the dependent variable
according to group status, and my hypothesis particularly predicts a difference
between the groups in trajectory of change at between specific ages. The data
shows a significant interaction between group and the linear and quadratic
effects of age, but I don't know if there is a way to assess this
interaction for one part of the age range, or if I need to be able to do so in
order to interpret my results as bing supportive of my hypothesis.
>
> Thanks for any help/advice!
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.


-- 

Bert Gunter
Genentech Nonclinical Biostatistics

Internal Contact Info:
Phone: 467-7374
Website:
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