On 2024-08-07 6:06 a.m., Brian Smith wrote:> Hi,
>
> I have performed ANOVA as below
>
> dat = data.frame(
> 'A' = c(-0.3960025, -0.3492880, -1.5893792, -1.4579074, -4.9214873,
> -0.8575018, -2.5551363, -0.9366557, -1.4307489, -0.3943704),
> 'B' = c(2,1,2,2,1,2,2,2,2,2),
> 'C' = c(0,1,1,1,1,1,1,0,1,1))
>
> summary(aov(A ~ B * C, dat))
>
> However now I also tried to calculate SSE for factor C
>
> Mean = sapply(split(dat, dat$C), function(x) mean(x$A))
> N = sapply(split(dat, dat$C), function(x) dim(x)[1])
>
> N[1] * (Mean[1] - mean(dat$A))^2 + N[2] * (Mean[2] - mean(dat$A))^2
> #1.691
>
> But in ANOVA table the sum-square for C is reported as 0.77.
>
> Could you please help how exactly this C = 0.77 is obtained from aov()
Your design isn't balanced, so there are several ways to calculate the
SS for C. What you have calculated looks like the "Type I SS" in SAS
notation, if I remember correctly, assuming that C enters the model
before B. That's not what R uses; I think it is Type II SS.
For some details about this, see
https://mcfromnz.wordpress.com/2011/03/02/anova-type-iiiiii-ss-explained/