On Fri, Feb 29, 2008 at 10:32 AM, Nauta, A.L. <[EMAIL PROTECTED]> wrote:
> I tried a 6-way anova, and indeed found out that changing the order of > factors influences the SS, F-ratio's and p-values. So what should I do if I > want to know which factor most strongly rejects H0? (H0 is the hypothese of > "no difference" in the population means) Should I better do 6 one-way > anova's (on each factor) and then compare the p-values? No. If you are going to try to perform a 6-way anova on an unbalanced data set you should read more about the analysis of variance so that you can understand the model and the hypotheses involved or ask a statistical consultant. This is not a topic that can be explained in a couple of email messages. You may find Bill Venables paper "Exegeses on Linear Models" (do an internet search on the title to find a copy) a good starting point. > ________________________________ > > From: [EMAIL PROTECTED] on behalf of Douglas Bates > Sent: Fri 29-2-2008 15:38 > To: Nauta, A.L. > Cc: R Help > > > Subject: Re: [R] unbalanced one-way ANOVA > > > > > > On Fri, Feb 29, 2008 at 4:47 AM, Nauta, A.L. <[EMAIL PROTECTED]> > wrote: > > > Thank you for your reply, > > is your answer (that the approach does not depend on balance in the data) > > only valid for one-way anova, or also for two-way or more-way anova? > > Any kind. > > You should be aware that for unbalanced data sets the sum of squares > attributed to a term depends on the order in which the terms occur in > the model. That is, the sum of squares and the F-ratios and the > p-values for, say, factor A will be different if you fit a model > > y ~ A + B > > versus the model > > y ~ B + A > > to a data set where factors A and B are unbalanced. > > This is because the sums of squares displayed by R's anova methods are > the sequential sums of squares. Although other statistical software > may calculate other, more exotic, types of sums of squares, many of us > would argue that these are the only ones that make sense. > > If in doubt about which sum of squares to use, the general rule is > that you should only pay attention to the F ratio and p-value for the > last term in the model. > > > ________________________________ > > From: [EMAIL PROTECTED] on behalf of Douglas Bates > > Sent: Fri 29-2-2008 0:39 > > To: Nauta, A.L. > > Cc: r-help@r-project.org > > Subject: Re: [R] unbalanced one-way ANOVA > > > > > > > > > > > > On Thu, Feb 28, 2008 at 7:52 AM, Nauta, A.L. <[EMAIL PROTECTED]> > > wrote: > > > Hi, > > > > > I have an unbalanced dataset on which I would like to perform a one-way > > anova test using R (aov). According to Wannacott and Wannacott (1990) p. > > 333, one-way anova with unbalanced data is possible with a few > modifications > > in the anova-calculations. The modified anova calculations should take > into > > account different sample sizes and a modified definition of the average. I > > was wondering if the aov-function in R is suitable for one-way anova on > > unbalanced data. > > > > Yes. > > > > The analysis of variance is performed in R by fitting a linear model > > created from indicator variables for the levels of the factor. This > > validity of this approach does not depend on balance in the data. > > > > The formulas given in an introductory textbook are almost never the > > way that results are computed in practice. I think we would all be > > better off if they didn't even give these misleading formulas. > > > ______________________________________________ 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.
