In proc glm, SAS will give both type I and type III sums of squares. You can get type II if you ask. Other procedures in SAS have different output as defaults.
Introductory textbooks may only cover type I SS. It is easy to calculate and gets the idea across. In application one of the problems is that a researcher could reanalyze the data to get an outcome of their choice because the order in which variables appear in the model influences their type I SS. A + B + A*B + C + A*C + B*C + A*B*C B + C + A + A*B + A*C + B*C + A*B*C Each variable (or interaction) can have a different type I SS and that can change the perception of which elements of the model are significant or not. Type III SS will give the same SS values for either model. Tim -----Original Message----- From: R-help <r-help-boun...@r-project.org> On Behalf Of Brian Smith Sent: Wednesday, August 7, 2024 8:28 AM To: Duncan Murdoch <murdoch.dun...@gmail.com> Cc: r-help@r-project.org Subject: Re: [R] Manually calculating values from aov() result [External Email] Hi, Thanks for this information. Is there any way to force R to use Type-1 SS? I think most textbooks use this only. Thanks and regards, On Wed, 7 Aug 2024 at 17:00, Duncan Murdoch <murdoch.dun...@gmail.com> wrote: > > 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://mcfr/ > omnz.wordpress.com%2F2011%2F03%2F02%2Fanova-type-iiiiii-ss-explained%2 > F&data=05%7C02%7Ctebert%40ufl.edu%7C21219670c5d541da503d08dcb6dc6c08%7 > C0d4da0f84a314d76ace60a62331e1b84%7C0%7C0%7C638586305046428793%7CUnkno > wn%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiL > CJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=HIGCrSH46P%2B1Y0cXUAfZ7DMCCORvtWaiRGC > crokr4Rs%3D&reserved=0 > ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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. ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.
