RE: [R] Help with three-way anova

From: michael watson (IAH-C) <michael.watson_at_bbsrc.ac.uk>
Date: Wed 06 Apr 2005 - 18:11:24 EST


OK, so I tried using lm() instead of aov() and they give similar results:

My.aov <- aov(IL.4 ~ Infected + Vaccinated + Lesions, data) My.lm <- lm(IL.4 ~ Infected + Vaccinated + Lesions, data)

If I do summary(My.lm) and summary(My.aov), I get similar results, but not identical.
If I do anova(My.aov) and anova(My.lm) I get identical results. I guess that's to be expected though.

Regarding the results of summary(My.lm), basically Intercept, Infected and Vaccinated are all significant at p<=0.05. I presume the signifcance of the Intercept is that it is significantly different to zero? How do I interpret that?

Many thanks
Mick

-----Original Message-----
From: Federico Calboli [mailto:f.calboli@imperial.ac.uk] Sent: 05 April 2005 16:33
To: michael watson (IAH-C)
Cc: r-help
Subject: Re: [R] Help with three-way anova

On Tue, 2005-04-05 at 15:51 +0100, michael watson (IAH-C) wrote:

> So, what I want to know is:
>
> 1) Given my unbalanced experimental design, is it valid to use aov?

I'd say no. Use lm() instead, save your analysis in an object and then possibly use drop1() to check the analysis

> 2) Have I used aov() correctly? If so, how do I get access results
> for interactions?

The use of aov() per se seems fine, but you did not put any interaction in the model... for that use factor * factor.

HTH, F

-- 
Federico C. F. Calboli
Department of Epidemiology and Public Health
Imperial College, St Mary's Campus
Norfolk Place, London W2 1PG

Tel  +44 (0)20 7594 1602     Fax (+44) 020 7594 3193

f.calboli [.a.t] imperial.ac.uk
f.calboli [.a.t] gmail.com

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Received on Wed Apr 06 18:15:40 2005

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