Hi, there
I am not a member on your mailing list, so could you please cc: a response
to me?
I am currently attempting to perform an ANOVA with both nested and normal
factors. My problem is that R is treating my nested factors the exact same
way as it would interaction terms.
My output for the nested model is as follows:
> nested <- anova(lm(ltotinv ~ habitat + fish/lake + habitat:fish +
habitat:(la\
ke %in% fish)))
> nested
Analysis of Variance Table
Response: ltotinv
Df Sum Sq Mean Sq F value Pr(>F)
habitat 1 17.0829 17.0829 50.0917 3.083e-09 ***
fish 1 0.9131 0.9131 2.6774 0.107600
habitat:fish 1 13.0100 13.0100 38.1488 8.877e-08 ***
fish:lake 1 1.0256 1.0256 3.0072 0.088599 .
habitat:fish:lake 1 2.7641 2.7641 8.1051 0.006229 **
Residuals 54 18.4158 0.3410
---lysis of Variance Table
Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` '
1
With just interactions, not nested:
> test <- anova(lm(ltotinv ~ habitat + fish + lake:fish + habitat:fish +
fish:h\
abitat:lake))
> test
Analysis of Variance Table
Response: ltotinv
Df Sum Sq Mean Sq F value Pr(>F)
habitat 1 17.0829 17.0829 50.0917 3.083e-09 ***
fish 1 0.9131 0.9131 2.6774 0.107600
habitat:fish 1 13.0100 13.0100 38.1488 8.877e-08 ***
fish:lake 1 1.0256 1.0256 3.0072 0.088599 .
habitat:fish:lake 1 2.7641 2.7641 8.1051 0.006229 **
Residuals 54 18.4158 0.3410
---
Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` '
1
>
We get the same answer. The reason I figured this out is because I did
this analysis first in SAS, and then tried to reproduce it in R. It must
be something to do with my syntax, I imagine, but I can't see what it is.
Any help anyone has would be greatly appreciated.
Sincerely,
Mike Rennie
M.Sc. Candidate, University of Toronto at Mississauga
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