Dear Thierry, That is the problem. I read that interpretation is the same, but the Intercept value of summary is different:
The mean of level "a" of f1 and level "I" of f2 (first level of each factor) is 0.7127851. When I run model with interaction term: summary.lm(aov(y~f1*f2,data=dt)) Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.7128 0.2884 2.471 0.0484 * f1b 1.0522 0.4560 2.307 0.0605 . f2II -0.6787 0.4560 -1.488 0.1872 f1b:f2II -1.1741 0.6449 -1.821 0.1185 I check that Intercept is mean of level "a" of f1 and level "I" of f2. But when I run the model without interaction term, the Intercept value is different: summary.lm(aov(y~f1+f2,data=dt)) Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.9476 0.2976 3.185 0.0154 * f1b 0.4651 0.3720 1.251 0.2513 f2II -1.2658 0.3720 -3.403 0.0114 * I do not know what is Intercept value in this case. I expected that it is mean of level "a" of f1 and level "I" of f2, but not. Best regards, Mario On 26 April 2015 at 12:30, Thierry Onkelinx <thierry.onkel...@inbo.be> wrote: > Dear Mario, > > The interpretation is the same: the average at the reference situation > which is the group that has f1 == "f1 level1" and f2 == "f2 level1". > > Best regards, > > ir. Thierry Onkelinx > Instituut voor natuur- en bosonderzoek / Research Institute for Nature and > Forest > team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance > Kliniekstraat 25 > 1070 Anderlecht > Belgium > > To call in the statistician after the experiment is done may be no more > than asking him to perform a post-mortem examination: he may be able to say > what the experiment died of. ~ Sir Ronald Aylmer Fisher > The plural of anecdote is not data. ~ Roger Brinner > The combination of some data and an aching desire for an answer does not > ensure that a reasonable answer can be extracted from a given body of data. > ~ John Tukey > > 2015-04-26 17:12 GMT+02:00 Mario José Marques-Azevedo < > mariojm...@gmail.com>: > >> Hi all, >> >> I am doing anova multi factor and I found different Intercept when model >> has interaction term. >> >> I have the follow data: >> >> set.seed(42) >> dt <- data.frame(f1=c(rep("a",5),rep("b",5)), >> f2=rep(c("I","II"),5), >> y=rnorm(10)) >> >> When I run >> >> summary.lm(aov(y ~ f1 * f2, data = dt)) >> >> The Intercept term is the mean of first level of f1 and f2. I can confirm >> that with: >> >> tapply(dt$y, list(dt$f1, dt$f2), mean) >> >> I know that others terms are difference of levels with Intercept. >> >> But I do not know what is Intercept when the model do not have interaction >> term: >> >> summary.lm(aov(y ~f1 + f2, data = dt)) >> >> I know that I can create a specific contrast table, by I would like >> understand the default R output. >> >> I read contrast sub-chapter on Crawley 2012 (The R book) and in his >> example >> the Intercept is different when model has or not interaction term, but he >> explain that Intercept is mean of first level of the factors. >> >> Best regards, >> >> Mario >> >> ............................................................. >> Mario José Marques-Azevedo >> Ph.D. Candidate in Ecology >> Dept. Plant Biology, Institute of Biology >> University of Campinas - UNICAMP >> Campinas, São Paulo, Brazil >> >> [[alternative HTML version deleted]] >> >> ______________________________________________ >> 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. > > > [[alternative HTML version deleted]] ______________________________________________ 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.