Dear [R] Users,
I have implemented a linear model with this syntax:
model<- lm (var_dependent ~ var_indipendent + factor + var_indipendent :
factor, dataframe)
anova (model)
Response: var_dependent
Df Sum Sq Mean Sq F value
Pr(>F)
var_indipendent 1 20.5522 20.5522 87.8701
1.167e-14 ***
factor 1 0.1060 0.1060 0.4530
0.50277
var_indipendent:factor 1 1.3861 1.3861 5..9261 0.01706
*
Residuals 83 19.4132 0.2339
---
Signif. codes: 0 *** 0.001 ** 0.01 * 0.05 . 0.1 1
The factor variable influence significatvly the regression. Which test I have
to use to understand whom factors (i.e. in my dataset factors are the different
sampling sites) influence the correlation?
Any suggestions how to perform post-hoc comparions?
Thanks a lot!
Francesco Nutini
P.S. numbers have no significance, it's just an example
[[alternative HTML version deleted]]
______________________________________________
R-help@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.
