Hi, I'm using the concurvity function to check for concurvity in my model. The output I get when comparing to the rest of the model (ie full=TRUE) many of the variables have concurvity values higher than 0.9. However when comparing the terms pairwise most values are very small, less than 0.1 (with the worst around 0.5). I am not sure where to go from here, should the full model output be cause for concern and should I refit the model eliminating some terms with high concurvity? or are the pairwise concurvities more informative? is there anything else I can do? The terms in the model are mostly interactions, with a few smooths and one parametric term. Thanks in advance
concurvity
2 messages · Eva Maria Leunissen, Bert Gunter
Eva: Yours is a statistical question, which is generally off topic here. While you may get a reply, I think you would do better to post on a statistics list like stats.stackexchange.com. Even better, I think, would be to consult a local statistical expert, as it sounds like you are fairly confused about the "concurvity" issues and may need a 1-1 discussion about what is appropriate in your application context. Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Mon, Feb 27, 2017 at 1:27 PM, Eva Maria Leunissen
<eva.leunissen at gmail.com> wrote:
Hi, I'm using the concurvity function to check for concurvity in my model.
The output I get when comparing to the rest of the model (ie full=TRUE)
many of the variables have concurvity values higher than 0.9. However when
comparing the terms pairwise most values are very small, less than 0.1
(with the worst around 0.5). I am not sure where to go from here, should
the full model output be cause for concern and should I refit the model
eliminating some terms with high concurvity? or are the pairwise
concurvities more informative?
is there anything else I can do? The terms in the model are mostly
interactions, with a few smooths and one parametric term.
Thanks in advance
[[alternative HTML version deleted]]
______________________________________________ R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.