Dear Diego, This is close enough to Spanish for me to understand it (I think).
Using Anova() in the car package for repeated-measures designs requires a multivariate linear model for all of the responses, which in turn requires that the data set be in "wide" format, with each response as a variable. In your case, there are two crossed within-subjects factors and no between-subjects factors. If this understanding is correct (but see below), then you could proceed as follows, where the crucial step is reshaping the data from "long" to "wide": ------------- snip -------------- Pa2$type.day <- with(Pa2, paste(Type, Day, sep=".")) (Wide <- reshape(Pa2, direction="wide", v.names="logbiovolume", idvar="Replicate", timevar="type.day", drop=c("Type", "Day"))) day <- ordered(rep(c(0, 2, 4), each=2)) type <- factor(rep(c("c", "t"), 3)) (idata <- data.frame(day, type)) mod <- lm(cbind(logbiovolume.c.0, logbiovolume.t.0, logbiovolume.c.2, logbiovolume.t.2, logbiovolume.c.4, logbiovolume.t.4) ~ 1, data=Wide) Anova(mod, idata=idata, idesign=~day*type) ------------- snip -------------- This serves to analyze the data that you showed; you'll have to adapt it for the full data set. I'm assuming that the "replicates" are independent units, and that the design is therefore entirely within replicate. If that's wrong, then the analysis I've suggested is also incorrect. I hope this helps, John ----------------------------------------------- John Fox Senator McMaster Professor of Social Statistics Department of Sociology McMaster University Hamilton, Ontario, Canada > -----Original Message----- > From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] > On Behalf Of Diego Pujoni > Sent: Friday, October 05, 2012 9:57 AM > To: r-help@r-project.org > Subject: [R] Dúvida função Anova pacote car - Medidas repetidas > > Ola pessoal, estou realizando uma ANOVA com medidas repetidas e estou > utilizando a fungco "Anova" do pacote "car". > > Medi o biovolume de algas a cada dois dias durante 10 dias (no banco de > dados abaixo ss coloquei ati o 40 dia). Tenho 2 tratamentos ("c","t") e > o > experimento foi realizado em triplicas ("A","B","C"). > > > Pa2 > Day Type Replicate logbiovolume > 1 0 c A 19.34 > 2 0 c B 18.27 > 3 0 c C 18.56 > 4 0 t A 18.41 > 5 0 t B 18.68 > 6 0 t C 18.86 > 7 2 c A 18.81 > 8 2 c B 18.84 > 9 2 c C 18.52 > 10 2 t A 18.29 > 11 2 t B 17.91 > 12 2 t C 17.67 > 13 4 c A 19.16 > 14 4 c B 18.85 > 15 4 c C 19.36 > 16 4 t A 19.05 > 17 4 t B 19.09 > 18 4 t C 18.26 > . > . > . > > Pa2.teste = within(Pa2,{group = factor(Type) > time = factor(Day) > id = factor(Replicate)}) > matrix = > with(Pa2.teste,cbind(Pa2[,VAR][group=="c"],Pa2[,VAR][group=="t"])) > matrix > [,1] [,2] > [1,] 19.34 18.41 > [2,] 18.27 18.68 > [3,] 18.56 18.86 > [4,] 18.81 18.29 > [5,] 18.84 17.91 > [6,] 18.52 17.67 > [7,] 19.16 19.05 > [8,] 18.85 19.09 > [9,] 19.36 18.26 > [10,] 19.63 18.96 > [11,] 19.94 18.06 > [12,] 19.54 18.37 > [13,] 19.98 17.96 > [14,] 20.99 17.93 > [15,] 20.45 17.74 > [16,] 21.12 17.60 > [17,] 21.66 17.33 > [18,] 21.51 18.12 > model <- lm(matrix ~ 1) > design <- factor(c("c","t")) > > options(contrasts=c("contr.sum", "contr.poly")) > aov <- Anova(model, idata=data.frame(design), idesign=~design, > type="III") > summary(aov, multivariate=F) > > Univariate Type III Repeated-Measures ANOVA Assuming Sphericity > > SS num Df Error SS den Df F Pr(>F) > (Intercept) 12951.2 1 6.3312 17 34775.336 < 2.2e-16 *** > design 19.1 1 17.3901 17 18.697 0.0004606 *** > --- > Signif. codes: 0 *** 0.001 ** 0.01 * 0.05 . 0.1 1 > > > O problema i que eu acho que esta fungco nco esta levando em > consideragco > os dias, nem as riplicas. Como fago para introduzir isto na analise. > Vocjs > conhecem alguma fungco correspondente nco paramitrica para este teste? > Tipo > um teste de Friedman com dois grupos (tratamento e riplica) e um bloco > (tempo)? > > Muito Obrigado > > Diego PJ > > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list 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.