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
-----Original Message-----
From: R-help <r-help-boun...@r-project.org> On Behalf Of Roland Sookias
Sent: Tuesday, July 16, 2024 12:08 PM
To: r-help@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]]
______________________________________________
R-help@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.
______________________________________________
R-help@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.
