Thank you Jari, So to test if there are significant interaction I should use Stage:Growhouse i.e. A:B. This will test the interaction and main effects that are marginal and so removed. How matters then if I include by="margin" or not? The R2 are the same (please see below) but the p-value changes. I assume the second way is most correct, is it?
*> adonis2(t(otu_fungi_out) ~ Stage : Growhouse, data=metadata_fungi_out, permutations=9999)* Permutation test for adonis under reduced model Terms added sequentially (first to last) Permutation: free Number of permutations: 9999 adonis2(formula = t(otu_fungi_out) ~ Stage:Growhouse, data = metadata_fungi_out, permutations = 9999) Df SumOfSqs R2 F Pr(>F) Stage:Growhouse 3 1.0812 0.23075 1.9998 0.0211 * Residual 20 3.6045 0.76925 Total 23 4.6857 1.00000 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 *> adonis2(t(otu_fungi_out) ~ Stage : Growhouse, data=metadata_fungi_out, by = "margin", permutations=9999)* Permutation test for adonis under reduced model Marginal effects of terms Permutation: free Number of permutations: 9999 adonis2(formula = t(otu_fungi_out) ~ Stage:Growhouse, data = metadata_fungi_out, permutations = 9999, by = "margin") Df SumOfSqs R2 F Pr(>F) Stage:Growhouse 3 1.0812 0.23075 1.9998 0.006 ** Residual 20 3.6045 0.76925 Total 23 4.6857 1.00000 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Cheers, Gian On Tue, 30 Oct 2018 at 05:47, Jari Oksanen <jari.oksa...@oulu.fi> wrote: > Hello Gian, > > These formulae expand into different models. Compare > > model.matrix(~ Stage:Growhouse, data=metadata_fungi_out) > model.matrix(~ Stage*Growhouse, data=metadata_fungi_out) > > The first model (Stage:Growhouse) will also contain (implicitly) main > effects and all these terms are marginal and can be removed, whereas the > latter Stage*Growhouse expands to explicit main effects and interaction > effects, and only the interaction effects are marginal and can be removed. > This is also reflected in the degrees of freedom in your anova table: In > the first case Stage:Growhouse has 3 df, and in the latter only 1 df (and > the main effects ignored had 2 df). > > Ciao, Giari > > > On 29 Oct 2018, at 19:11, Gian Maria Niccolò Benucci < > gian.benu...@gmail.com> wrote: > > > > Hello Jari, > > > > It is a little bit confusing. If A*B unfolds in A+B+A:B then A:B is the > > real interaction component. > > So, which if the code below will test the variance for the interaction > > alone? > > > >> adonis2(t(otu_fungi_out) ~ *Stage : Growhouse*, data=metadata_fungi_out, > > by = "margin", permutations=9999) > > Permutation test for adonis under reduced model > > Marginal effects of terms > > Permutation: free > > Number of permutations: 9999 > > > > adonis2(formula = t(otu_fungi_out) ~ Stage:Growhouse, data = > > metadata_fungi_out, permutations = 9999, by = "margin") > > Df SumOfSqs R2 F Pr(>F) > > Stage:Growhouse 3 1.0812 0.23075 1.9998 1e-04 *** > > Residual 20 3.6045 0.76925 > > Total 23 4.6857 1.00000 > > --- > > Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 > > > > > >> adonis2(t(otu_fungi_out) ~ *Stage * Growhouse*, data=metadata_fungi_out, > > by = "margin", permutations=9999) > > Permutation test for adonis under reduced model > > Marginal effects of terms > > Permutation: free > > Number of permutations: 9999 > > > > adonis2(formula = t(otu_fungi_out) ~ Stage * Growhouse, data = > > metadata_fungi_out, permutations = 9999, by = "margin") > > Df SumOfSqs R2 F Pr(>F) > > Stage:Growhouse 1 0.2171 0.04633 1.2045 0.2443 > > Residual 20 3.6045 0.76925 > > Total 23 4.6857 1.00000 > >> > > > > The results is clearly very different. Also, in a normal adonis call I > > didn't have any significance for the interaction that I have instead if I > > use A:B. So ~ A*B will not test for interactions at all? > > > >> *adonis*(t(otu_fungi_out) ~ Stage * Growhouse, data=metadata_fungi_out, > > permutations=9999) > > Call: > > adonis(formula = t(otu_fungi_out) ~ Stage * Growhouse, data = > > metadata_fungi_out, permutations = 9999) > > > > Permutation: free > > Number of permutations: 9999 > > > > Terms added sequentially (first to last) > > > > Df SumsOfSqs MeanSqs F.Model R2 Pr(>F) > > Stage 1 0.4877 0.48769 2.7060 0.10408 0.0247 * > > Growhouse 1 0.3765 0.37647 2.0889 0.08034 0.0542 . > > Stage:Growhouse 1 0.2171 0.21708 1.2045 0.04633 0.2507 > > Residuals 20 3.6045 0.18023 0.76925 > > Total 23 4.6857 1.00000 > > --- > > Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 > >> > > > > Thank you! > > > > Gian > > > > > > > > > > > > On Tue, 16 Oct 2018 at 08:54, Jari Oksanen <jari.oksa...@oulu.fi> wrote: > > > >> > >> > >> On 16/10/18 11:23, Torsten Hauffe wrote: > >>> "adonis2(speciesdataset~A*B, by="margin") but then only the effect of > >> the > >>> interaction is tested." > >>> > >>> This is not entirely correct. > >>> adonis2(speciesdataset~A:B, by="margin") would test the interaction > >> alone. > >>> ~A*B unfolds to ~A+B+A:B > >> > >> Well, it was correct: the only **marginal** effect in ~A+B+A:B is A:B (A > >> and B are not marginal), and by = "margin" will only analyse marginal > >> effects. > >> > >> Cheers, Jari Oksanen > >>> > >>> On Tue, 16 Oct 2018 at 11:51, Ellen Pape <ellen.p...@gmail.com> wrote: > >>> > >>>> Hi all, > >>>> > >>>> I don't know whether this is the correct mailing group to address this > >>>> question: > >>>> > >>>> I would like to perform a 2-way permanova analysis in R (using adonis > in > >>>> vegan). By default you are performing sequential tests (by="terms"), > so > >>>> when you have 2 or more factors, the order of these factors matter. > >>>> However, since I wanted to circumvent this, I chose for the option > >>>> by="margin" (adonis2(speciesdataset~A*B, by="margin")) but then only > the > >>>> effect of the interaction is tested. On the "help page" of anova. cca > it > >>>> says: "if you select by="margin" -> the current function only > evaluates > >>>> marginal terms. It will, for instance, ignore main effects that are > >>>> included in interaction terms." > >>>> > >>>> > >>>> My question now is: can I somehow get the main effects tested anyhow, > >> when > >>>> the interaction term is not significant? > >>>> > >>>> Thanks, > >>>> Ellen > >>>> > >>>> [[alternative HTML version deleted]] > >>>> > >>>> _______________________________________________ > >>>> R-sig-ecology mailing list > >>>> R-sig-ecology@r-project.org > >>>> https://stat.ethz.ch/mailman/listinfo/r-sig-ecology > >>>> > >>> > >>> [[alternative HTML version deleted]] > >>> > >>> _______________________________________________ > >>> R-sig-ecology mailing list > >>> R-sig-ecology@r-project.org > >>> https://stat.ethz.ch/mailman/listinfo/r-sig-ecology > >>> > >> _______________________________________________ > >> R-sig-ecology mailing list > >> R-sig-ecology@r-project.org > >> https://stat.ethz.ch/mailman/listinfo/r-sig-ecology > >> > > > > [[alternative HTML version deleted]] > > > > _______________________________________________ > > R-sig-ecology mailing list > > R-sig-ecology@r-project.org > > https://stat.ethz.ch/mailman/listinfo/r-sig-ecology > > -- Gian Maria Niccolò Benucci, Ph.D. Postdoctoral research associate Michigan State University Department of Plant, Soil and Microbial Sciences 1066 Bogue Street 48825 East Lansing, MI Lab: +1 (517) 844-6966 Email: gian.benu...@gmail.com *----- Do not print this email unless you really need to. 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