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!
Testing significance of interaction between group and longitudinal change for part of the age range in a mixed linear model
2 messages · Angela Brant, Bert Gunter
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: http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm