Dear all I have undertaken some phylogenetic and non-phylogenetic regressions with gls() in nlme with single preictor variables. A p value is associated with the intercept (upper p value) and another with the predictor variable (lower). Which p value is important? What does it mean if the intercept p value is insignificant but the predictor is still significant? Thanks a lot, and sorry for my ignorance, Roland [[alternative HTML version deleted]]
Yikes! This list is for help on R *programming*, not statistics per se, although these do sometimes intersect. However, your query strikes me as a request for a kind of statistical tutorial, which is OT here. Just so you are aware... R has a special interest group (SIG) for phylgenetics at https://stat.ethz.ch/mailman/listinfo/r-sig-phylo . I think this would be a better place for you to post, as relevant expertise should be found there. However, I do not know how active that list is, so maybe not. Good luck. Cheers, Bert On Tue, Jul 16, 2024 at 3:10?PM Roland Sookias <r.sookias at gmail.com> wrote:> > Dear all > > I have undertaken some phylogenetic and non-phylogenetic regressions with > gls() in nlme with single preictor variables. A p value is associated with > the intercept (upper p value) and another with the predictor variable > (lower). Which p value is important? What does it mean if the intercept p > value is insignificant but the predictor is still significant? > > Thanks a lot, and sorry for my ignorance, > > Roland > > [[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.
In a lm() model a significant intercept means that the line passes above or
below the intercept (x=0, y=0). A significant predictor means that the slope is
not zero. More generally the significant predictor means that the predictor has
some influence on the predicted. With nlme() the relationship may not be linear.
Your result indicates that you cannot tell if the relationship passes through
the origin or not, but the predictor has a significant influence on the
predicted.
Tim
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From: R-help <r-help-bounces at r-project.org> On Behalf Of Roland Sookias
Sent: Tuesday, July 16, 2024 12:08 PM
To: r-help at r-project.org
Subject: [R] Interpreting p values of gls in nlme
[External Email]
Dear all
I have undertaken some phylogenetic and non-phylogenetic regressions with
gls() in nlme with single preictor variables. A p value is associated with the
intercept (upper p value) and another with the predictor variable (lower). Which
p value is important? What does it mean if the intercept p value is
insignificant but the predictor is still significant?
Thanks a lot, and sorry for my ignorance,
Roland
[[alternative HTML version deleted]]
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PLEASE do read the posting guide http://www.r-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.