From the documentation for anova()
:
When given a sequence of objects, ‘anova’ tests the models against one another in the order specified...
What does it mean to test the models against one another? And why does the order matter?
Here is an example from the GenABEL tutorial:
> modelGen = lm(qt~snp1)
> modelAdd = lm(qt~as.numeric(snp1))
> modelDom = lm(qt~I(as.numeric(snp1)>=2))
> modelRec = lm(qt~I(as.numeric(snp1)>=3))
anova(modelAdd, modelGen, test="Chisq")
Analysis of Variance Table
Model 1: qt ~ as.numeric(snp1)
Model 2: qt ~ snp1
Res.Df RSS Df Sum of Sq Pr(>Chi)
1 2372 2320
2 2371 2320 1 0.0489 0.82
anova(modelDom, modelGen, test="Chisq")
Analysis of Variance Table
Model 1: qt ~ I(as.numeric(snp1) >= 2)
Model 2: qt ~ snp1
Res.Df RSS Df Sum of Sq Pr(>Chi)
1 2372 2322
2 2371 2320 1 1.77 0.18
anova(modelRec, modelGen, test="Chisq")
Analysis of Variance Table
Model 1: qt ~ I(as.numeric(snp1) >= 3)
Model 2: qt ~ snp1
Res.Df RSS Df Sum of Sq Pr(>Chi)
1 2372 2324
2 2371 2320 1 3.53 0.057 .
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Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
How do I interpret this output?