
12

Hi all,
I don't know whether this is the correct mailing group to address this
question:
I would like to perform a 2way 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]]
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Rsigecology mailing list
[hidden email]
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"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
On Tue, 16 Oct 2018 at 11:51, Ellen Pape < [hidden email]> wrote:
> Hi all,
>
> I don't know whether this is the correct mailing group to address this
> question:
>
> I would like to perform a 2way 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]]
>
> _______________________________________________
> Rsigecology mailing list
> [hidden email]
> https://stat.ethz.ch/mailman/listinfo/rsigecology>
[[alternative HTML version deleted]]
_______________________________________________
Rsigecology mailing list
[hidden email]
https://stat.ethz.ch/mailman/listinfo/rsigecology


El 16/10/2018 a las 11:51, Ellen Pape escribió:
> Hi all,
>
Maybe adonis2(speciesdataset~ A + B, by="margin") ?
> I don't know whether this is the correct mailing group to address this
> question:
>
> I would like to perform a 2way 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]]
>
> _______________________________________________
> Rsigecology mailing list
> [hidden email]
> https://stat.ethz.ch/mailman/listinfo/rsigecology> .
>

Marcelino de la Cruz Rot
Depto. de Biología y Geología
Física y Química Inorgánica
Universidad Rey Juan Carlos
Móstoles España
_______________________________________________
Rsigecology mailing list
[hidden email]
https://stat.ethz.ch/mailman/listinfo/rsigecology


Hi,
Yes, but is there no way of testing for the main effects and interaction
simultaneously?
I also thought of first testing the interaction: adonis2(speciesdataset~ A
*** B, by="margin") , and then  if the interaction is not significant
testing for the main effects by adonis2(speciesdataset~ A *+* B,
by="margin") . Is this "allowed"?
Thanks,
Ellen
On Tue, 16 Oct 2018 at 12:01, Marcelino De La Cruz Rot <
[hidden email]> wrote:
> El 16/10/2018 a las 11:51, Ellen Pape escribió:
> > Hi all,
> >
> Maybe adonis2(speciesdataset~ A + B, by="margin") ?
>
>
>
> > I don't know whether this is the correct mailing group to address this
> > question:
> >
> > I would like to perform a 2way 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]]
> >
> > _______________________________________________
> > Rsigecology mailing list
> > [hidden email]
> > https://stat.ethz.ch/mailman/listinfo/rsigecology> > .
> >
>
> 
> Marcelino de la Cruz Rot
> Depto. de Biología y Geología
> Física y Química Inorgánica
> Universidad Rey Juan Carlos
> Móstoles España
>
>
[[alternative HTML version deleted]]
_______________________________________________
Rsigecology mailing list
[hidden email]
https://stat.ethz.ch/mailman/listinfo/rsigecology


El 16/10/2018 a las 12:09, Ellen Pape escribió:
> Hi,
>
> Yes, but is there no way of testing for the main effects and
> interaction simultaneously?
In general, this is "not allowed", to say it with your words.
>
> I also thought of first testing the interaction:
> adonis2(speciesdataset~ A *** B, by="margin") , and then  if the
> interaction is not significant testing for the main effects by
> adonis2(speciesdataset~ A *+* B, by="margin") . Is this "allowed"?
This is analogous to, e.g., an ANCOVA, isn't it? Therefore it makes
quite sense.
>
> Thanks,
> Ellen
>
> On Tue, 16 Oct 2018 at 12:01, Marcelino De La Cruz Rot
> < [hidden email] <mailto: [hidden email]>> wrote:
>
> El 16/10/2018 a las 11:51, Ellen Pape escribió:
> > Hi all,
> >
> Maybe adonis2(speciesdataset~ A + B, by="margin") ?
>
>
>
> > I don't know whether this is the correct mailing group to
> address this
> > question:
> >
> > I would like to perform a 2way 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]]
> >
> > _______________________________________________
> > Rsigecology mailing list
> > [hidden email] <mailto: [hidden email]>
> > https://stat.ethz.ch/mailman/listinfo/rsigecology> > .
> >
>
> 
> Marcelino de la Cruz Rot
> Depto. de Biología y Geología
> Física y Química Inorgánica
> Universidad Rey Juan Carlos
> Móstoles España
>

Marcelino de la Cruz Rot
Depto. de Biología y Geología
Física y Química Inorgánica
Universidad Rey Juan Carlos
Móstoles España
_______________________________________________
Rsigecology mailing list
[hidden email]
https://stat.ethz.ch/mailman/listinfo/rsigecology


Hi,
I know that A*B = A+B+A:B, but in this case, i.e. doing an adonis2 and
specifying by="terms" will only do the test for the interaction, not the
main effects. If one chooses by="terms", you will get a test for the main
effects and the interaction, but than the order of factors matters.
Best regards
Ellen
On Tue, 16 Oct 2018 at 12:23, Torsten Hauffe < [hidden email]>
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
>
> On Tue, 16 Oct 2018 at 11:51, Ellen Pape < [hidden email]> wrote:
>
>> Hi all,
>>
>> I don't know whether this is the correct mailing group to address this
>> question:
>>
>> I would like to perform a 2way 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]]
>>
>> _______________________________________________
>> Rsigecology mailing list
>> [hidden email]
>> https://stat.ethz.ch/mailman/listinfo/rsigecology>>
>
[[alternative HTML version deleted]]
_______________________________________________
Rsigecology mailing list
[hidden email]
https://stat.ethz.ch/mailman/listinfo/rsigecology


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 < [hidden email]> wrote:
>
>> Hi all,
>>
>> I don't know whether this is the correct mailing group to address this
>> question:
>>
>> I would like to perform a 2way 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]]
>>
>> _______________________________________________
>> Rsigecology mailing list
>> [hidden email]
>> https://stat.ethz.ch/mailman/listinfo/rsigecology>>
>
> [[alternative HTML version deleted]]
>
> _______________________________________________
> Rsigecology mailing list
> [hidden email]
> https://stat.ethz.ch/mailman/listinfo/rsigecology>
_______________________________________________
Rsigecology mailing list
[hidden email]
https://stat.ethz.ch/mailman/listinfo/rsigecology


I see. Thanks for explaining Jari!
On Tue, 16 Oct 2018 at 14:54, Jari Oksanen < [hidden email]> 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 < [hidden email]> wrote:
> >
> >> Hi all,
> >>
> >> I don't know whether this is the correct mailing group to address this
> >> question:
> >>
> >> I would like to perform a 2way 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]]
> >>
> >> _______________________________________________
> >> Rsigecology mailing list
> >> [hidden email]
> >> https://stat.ethz.ch/mailman/listinfo/rsigecology> >>
> >
> > [[alternative HTML version deleted]]
> >
> > _______________________________________________
> > Rsigecology mailing list
> > [hidden email]
> > https://stat.ethz.ch/mailman/listinfo/rsigecology> >
> _______________________________________________
> Rsigecology mailing list
> [hidden email]
> https://stat.ethz.ch/mailman/listinfo/rsigecology>
[[alternative HTML version deleted]]
_______________________________________________
Rsigecology mailing list
[hidden email]
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vegan::adonis2 only handles marginal effects with by = “margin” (and hence only term A:B of A*B), but RVAideMemoire package has function adonis.II that also can do “type II” and “type III” tests (what ever these mean with adonis) which may be something you are looking for. I haven’t checked how these tests were implemented, but you may do that in your leisure if you think this is what you want to have.
Cheers, Jari Oksanen
> On 16 Oct 2018, at 14:53 pm, Ellen Pape < [hidden email]> wrote:
>
> Hi,
>
> I know that A*B = A+B+A:B, but in this case, i.e. doing an adonis2 and
> specifying by="terms" will only do the test for the interaction, not the
> main effects. If one chooses by="terms", you will get a test for the main
> effects and the interaction, but than the order of factors matters.
>
> Best regards
> Ellen
>
> On Tue, 16 Oct 2018 at 12:23, Torsten Hauffe < [hidden email]>
> 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
>>
>> On Tue, 16 Oct 2018 at 11:51, Ellen Pape < [hidden email]> wrote:
>>
>>> Hi all,
>>>
>>> I don't know whether this is the correct mailing group to address this
>>> question:
>>>
>>> I would like to perform a 2way 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]]
>>>
>>> _______________________________________________
>>> Rsigecology mailing list
>>> [hidden email]
>>> https://stat.ethz.ch/mailman/listinfo/rsigecology>>>
>>
>
> [[alternative HTML version deleted]]
>
> _______________________________________________
> Rsigecology mailing list
> [hidden email]
> https://stat.ethz.ch/mailman/listinfo/rsigecology_______________________________________________
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[hidden email]
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ok, thanks, I'll check it out!
On Tue, 16 Oct 2018 at 17:16, Jari Oksanen < [hidden email]> wrote:
> vegan::adonis2 only handles marginal effects with by = “margin” (and hence
> only term A:B of A*B), but RVAideMemoire package has function adonis.II
> that also can do “type II” and “type III” tests (what ever these mean with
> adonis) which may be something you are looking for. I haven’t checked how
> these tests were implemented, but you may do that in your leisure if you
> think this is what you want to have.
>
> Cheers, Jari Oksanen
>
> > On 16 Oct 2018, at 14:53 pm, Ellen Pape < [hidden email]> wrote:
> >
> > Hi,
> >
> > I know that A*B = A+B+A:B, but in this case, i.e. doing an adonis2 and
> > specifying by="terms" will only do the test for the interaction, not the
> > main effects. If one chooses by="terms", you will get a test for the main
> > effects and the interaction, but than the order of factors matters.
> >
> > Best regards
> > Ellen
> >
> > On Tue, 16 Oct 2018 at 12:23, Torsten Hauffe < [hidden email]>
> > 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
> >>
> >> On Tue, 16 Oct 2018 at 11:51, Ellen Pape < [hidden email]> wrote:
> >>
> >>> Hi all,
> >>>
> >>> I don't know whether this is the correct mailing group to address this
> >>> question:
> >>>
> >>> I would like to perform a 2way 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]]
> >>>
> >>> _______________________________________________
> >>> Rsigecology mailing list
> >>> [hidden email]
> >>> https://stat.ethz.ch/mailman/listinfo/rsigecology> >>>
> >>
> >
> > [[alternative HTML version deleted]]
> >
> > _______________________________________________
> > Rsigecology mailing list
> > [hidden email]
> > https://stat.ethz.ch/mailman/listinfo/rsigecology>
>
[[alternative HTML version deleted]]
_______________________________________________
Rsigecology mailing list
[hidden email]
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Hello all,
thank you for the interesting discussion on the topic. I have an additional
question that i thought would worth to ask directly here instead of opening
a new thread for it. How sensitive is adonis() to differences in sample
numbers of the groups I am comparing? To be more precise, I am trying to
compare the microbial communities in 3 groups of samples (my treatments)
and they have 22, 24, and 24 samples each. I have always thought that an
even design would have been the rule but I found several comments online
that made are confounding.
Thank you for your help!
Gian
On Wed, 17 Oct 2018 at 08:51, Ellen Pape < [hidden email]> wrote:
> ok, thanks, I'll check it out!
>
> On Tue, 16 Oct 2018 at 17:16, Jari Oksanen < [hidden email]> wrote:
>
> > vegan::adonis2 only handles marginal effects with by = “margin” (and
> hence
> > only term A:B of A*B), but RVAideMemoire package has function adonis.II
> > that also can do “type II” and “type III” tests (what ever these mean
> with
> > adonis) which may be something you are looking for. I haven’t checked how
> > these tests were implemented, but you may do that in your leisure if you
> > think this is what you want to have.
> >
> > Cheers, Jari Oksanen
> >
> > > On 16 Oct 2018, at 14:53 pm, Ellen Pape < [hidden email]> wrote:
> > >
> > > Hi,
> > >
> > > I know that A*B = A+B+A:B, but in this case, i.e. doing an adonis2 and
> > > specifying by="terms" will only do the test for the interaction, not
> the
> > > main effects. If one chooses by="terms", you will get a test for the
> main
> > > effects and the interaction, but than the order of factors matters.
> > >
> > > Best regards
> > > Ellen
> > >
> > > On Tue, 16 Oct 2018 at 12:23, Torsten Hauffe < [hidden email]
> >
> > > 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
> > >>
> > >> On Tue, 16 Oct 2018 at 11:51, Ellen Pape < [hidden email]>
> wrote:
> > >>
> > >>> Hi all,
> > >>>
> > >>> I don't know whether this is the correct mailing group to address
> this
> > >>> question:
> > >>>
> > >>> I would like to perform a 2way 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]]
> > >>>
> > >>> _______________________________________________
> > >>> Rsigecology mailing list
> > >>> [hidden email]
> > >>> https://stat.ethz.ch/mailman/listinfo/rsigecology> > >>>
> > >>
> > >
> > > [[alternative HTML version deleted]]
> > >
> > > _______________________________________________
> > > Rsigecology mailing list
> > > [hidden email]
> > > https://stat.ethz.ch/mailman/listinfo/rsigecology> >
> >
>
> [[alternative HTML version deleted]]
>
> _______________________________________________
> Rsigecology mailing list
> [hidden email]
> https://stat.ethz.ch/mailman/listinfo/rsigecology [[alternative HTML version deleted]]
_______________________________________________
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[hidden email]
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In reply to this post by Marcelino De La Cruz Rot
Hello,
Yes, but is there no way of testing for the main effects and
> interaction simultaneously?
In general, this is "not allowed", to say it with your words.
OK, but this is done in general ANOVAs, no? test for interaction and main
effects simultaneously (and then if you have a sign interaction term, you
cannot interpret the tests for the main effects)  at least that is how I
was taught how to do this (but maybe this is wrong?)
FYI  package "RVAideMemoire" does indeed contain a function to perform
type II adonis tests ("adonis.II"), but no type III tests..
best wishes to all,
Ellen
On Tue, 16 Oct 2018 at 12:24, Marcelino De La Cruz Rot <
[hidden email]> wrote:
> El 16/10/2018 a las 12:09, Ellen Pape escribió:
> > Hi,
> >
> > Yes, but is there no way of testing for the main effects and
> > interaction simultaneously?
>
> In general, this is "not allowed", to say it with your words.
>
> >
> > I also thought of first testing the interaction:
> > adonis2(speciesdataset~ A *** B, by="margin") , and then  if the
> > interaction is not significant testing for the main effects by
> > adonis2(speciesdataset~ A *+* B, by="margin") . Is this "allowed"?
>
> This is analogous to, e.g., an ANCOVA, isn't it? Therefore it makes
> quite sense.
>
>
> >
> > Thanks,
> > Ellen
> >
> > On Tue, 16 Oct 2018 at 12:01, Marcelino De La Cruz Rot
> > < [hidden email] <mailto: [hidden email]>> wrote:
> >
> > El 16/10/2018 a las 11:51, Ellen Pape escribió:
> > > Hi all,
> > >
> > Maybe adonis2(speciesdataset~ A + B, by="margin") ?
> >
> >
> >
> > > I don't know whether this is the correct mailing group to
> > address this
> > > question:
> > >
> > > I would like to perform a 2way 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]]
> > >
> > > _______________________________________________
> > > Rsigecology mailing list
> > > [hidden email] <mailto: [hidden email]>
> > > https://stat.ethz.ch/mailman/listinfo/rsigecology> > > .
> > >
> >
> > 
> > Marcelino de la Cruz Rot
> > Depto. de Biología y Geología
> > Física y Química Inorgánica
> > Universidad Rey Juan Carlos
> > Móstoles España
> >
>
> 
> Marcelino de la Cruz Rot
> Depto. de Biología y Geología
> Física y Química Inorgánica
> Universidad Rey Juan Carlos
> Móstoles España
>
>
[[alternative HTML version deleted]]
_______________________________________________
Rsigecology mailing list
[hidden email]
https://stat.ethz.ch/mailman/listinfo/rsigecology


El 24/10/2018 a las 10:29, Ellen Pape escribió:
> Hello,
>
> Yes, but is there no way of testing for the main effects and
>
> > interaction simultaneously?
> In general, this is "not allowed", to say it with your words.
>
> OK, but this is done in general ANOVAs, no? test for interaction and
> main effects simultaneously (and then if you have a sign interaction
> term, you cannot interpret the tests for the main effects)  at least
> that is how I was taught how to do this (but maybe this is wrong?)
You are completely right. Maybe I misunderstood you as, in my opinion,
the tests is for the interaction only (even with the main effects
included in the model), not "for the main effects and the interaction
simultaneously".
>
> FYI  package "RVAideMemoire" does indeed contain a function to
> perform type II adonis tests ("adonis.II"), but no type III tests..
Interesting. But this is the same as adonis2(formula, by="margin"),
isn't it?
Cheers,
Marcelino
>
> best wishes to all,
> Ellen
> On Tue, 16 Oct 2018 at 12:24, Marcelino De La Cruz Rot
> < [hidden email] <mailto: [hidden email]>> wrote:
>
> El 16/10/2018 a las 12:09, Ellen Pape escribió:
> > Hi,
> >
> > Yes, but is there no way of testing for the main effects and
> > interaction simultaneously?
>
> In general, this is "not allowed", to say it with your words.
>
> >
> > I also thought of first testing the interaction:
> > adonis2(speciesdataset~ A *** B, by="margin") , and then  if the
> > interaction is not significant testing for the main effects by
> > adonis2(speciesdataset~ A *+* B, by="margin") . Is this "allowed"?
>
> This is analogous to, e.g., an ANCOVA, isn't it? Therefore it makes
> quite sense.
>
>
> >
> > Thanks,
> > Ellen
> >
> > On Tue, 16 Oct 2018 at 12:01, Marcelino De La Cruz Rot
> > < [hidden email] <mailto: [hidden email]>
> <mailto: [hidden email]
> <mailto: [hidden email]>>> wrote:
> >
> > El 16/10/2018 a las 11:51, Ellen Pape escribió:
> > > Hi all,
> > >
> > Maybe adonis2(speciesdataset~ A + B, by="margin") ?
> >
> >
> >
> > > I don't know whether this is the correct mailing group to
> > address this
> > > question:
> > >
> > > I would like to perform a 2way 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]]
> > >
> > > _______________________________________________
> > > Rsigecology mailing list
> > > [hidden email]
> <mailto: [hidden email]>
> <mailto: [hidden email]
> <mailto: [hidden email]>>
> > > https://stat.ethz.ch/mailman/listinfo/rsigecology> > > .
> > >
> >
> > 
> > Marcelino de la Cruz Rot
> > Depto. de Biología y Geología
> > Física y Química Inorgánica
> > Universidad Rey Juan Carlos
> > Móstoles España
> >
>
> 
> Marcelino de la Cruz Rot
> Depto. de Biología y Geología
> Física y Química Inorgánica
> Universidad Rey Juan Carlos
> Móstoles España
>

Marcelino de la Cruz Rot
Depto. de Biología y Geología
Física y Química Inorgánica
Universidad Rey Juan Carlos
Móstoles España
_______________________________________________
Rsigecology mailing list
[hidden email]
https://stat.ethz.ch/mailman/listinfo/rsigecology


Hi, see my answer concerning the adonis.II below
On Wed, 24 Oct 2018 at 10:58, Marcelino De La Cruz Rot <
[hidden email]> wrote:
> El 24/10/2018 a las 10:29, Ellen Pape escribió:
> > Hello,
> >
> > Yes, but is there no way of testing for the main effects and
> >
> > > interaction simultaneously?
> > In general, this is "not allowed", to say it with your words.
> >
> > OK, but this is done in general ANOVAs, no? test for interaction and
> > main effects simultaneously (and then if you have a sign interaction
> > term, you cannot interpret the tests for the main effects)  at least
> > that is how I was taught how to do this (but maybe this is wrong?)
>
> You are completely right. Maybe I misunderstood you as, in my opinion,
> the tests is for the interaction only (even with the main effects
> included in the model), not "for the main effects and the interaction
> simultaneously".
>
> >
>
>> > FYI  package "RVAideMemoire" does indeed contain a function to
>> > perform type II adonis tests ("adonis.II"), but no type III tests..
>> Interesting. But this is the same as adonis2(formula, by="margin"),
>> isn't it?
>
>
> well, I don't think this is the same, but I don't fully understand, to be
honest. adonis2, "by=margin" for a 2way permanova tests the effect of the
interaction only between the 2 factors/terms (but is still type I SS?).
adonis.II does a type II SS, for which you get a test for the main effects
and the interaction, but here the order of the terms/factors does not
matter (in contrast to adonis2, by="terms"). Ror the type II SS (and thus
adonis).II, each main effect is tested for after the other main effect, and
the interaction is assumed to be nonsignificant. The SS for main effect of
a factor is not adjusted for any interactions involving that factor. (this
is info I got from the internet)
I am still puzzled about what would be the best way to analyze my data, but
I have already requested a consult with our statistical dept, so hopefully
they can help me out :)
Best regards,
Ellen
> Cheers,
>
> Marcelino
>
>
> >
> > best wishes to all,
> > Ellen
> > On Tue, 16 Oct 2018 at 12:24, Marcelino De La Cruz Rot
> > < [hidden email] <mailto: [hidden email]>> wrote:
> >
> > El 16/10/2018 a las 12:09, Ellen Pape escribió:
> > > Hi,
> > >
> > > Yes, but is there no way of testing for the main effects and
> > > interaction simultaneously?
> >
> > In general, this is "not allowed", to say it with your words.
> >
> > >
> > > I also thought of first testing the interaction:
> > > adonis2(speciesdataset~ A *** B, by="margin") , and then  if the
> > > interaction is not significant testing for the main effects by
> > > adonis2(speciesdataset~ A *+* B, by="margin") . Is this "allowed"?
> >
> > This is analogous to, e.g., an ANCOVA, isn't it? Therefore it makes
> > quite sense.
> >
> >
> > >
> > > Thanks,
> > > Ellen
> > >
> > > On Tue, 16 Oct 2018 at 12:01, Marcelino De La Cruz Rot
> > > < [hidden email] <mailto: [hidden email]>
> > <mailto: [hidden email]
> > <mailto: [hidden email]>>> wrote:
> > >
> > > El 16/10/2018 a las 11:51, Ellen Pape escribió:
> > > > Hi all,
> > > >
> > > Maybe adonis2(speciesdataset~ A + B, by="margin") ?
> > >
> > >
> > >
> > > > I don't know whether this is the correct mailing group to
> > > address this
> > > > question:
> > > >
> > > > I would like to perform a 2way 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]]
> > > >
> > > > _______________________________________________
> > > > Rsigecology mailing list
> > > > [hidden email]
> > <mailto: [hidden email]>
> > <mailto: [hidden email]
> > <mailto: [hidden email]>>
> > > > https://stat.ethz.ch/mailman/listinfo/rsigecology> > > > .
> > > >
> > >
> > > 
> > > Marcelino de la Cruz Rot
> > > Depto. de Biología y Geología
> > > Física y Química Inorgánica
> > > Universidad Rey Juan Carlos
> > > Móstoles España
> > >
> >
> > 
> > Marcelino de la Cruz Rot
> > Depto. de Biología y Geología
> > Física y Química Inorgánica
> > Universidad Rey Juan Carlos
> > Móstoles España
> >
>
> 
> Marcelino de la Cruz Rot
> Depto. de Biología y Geología
> Física y Química Inorgánica
> Universidad Rey Juan Carlos
> Móstoles España
>
>
[[alternative HTML version deleted]]
_______________________________________________
Rsigecology mailing list
[hidden email]
https://stat.ethz.ch/mailman/listinfo/rsigecology


Hi Jari,
adonis.II in package RVAideMemoire only performs type II SS tests, not type
III. I have googled and could not find any package that contains a type III
adonis test. Any plans for adjusting adonis in vegan for also including
type III tests, by any chance? :)
Thanks!
Ellen
On Tue, 16 Oct 2018 at 17:16, Jari Oksanen < [hidden email]> wrote:
> vegan::adonis2 only handles marginal effects with by = “margin” (and hence
> only term A:B of A*B), but RVAideMemoire package has function adonis.II
> that also can do “type II” and “type III” tests (what ever these mean with
> adonis) which may be something you are looking for. I haven’t checked how
> these tests were implemented, but you may do that in your leisure if you
> think this is what you want to have.
>
> Cheers, Jari Oksanen
>
> > On 16 Oct 2018, at 14:53 pm, Ellen Pape < [hidden email]> wrote:
> >
> > Hi,
> >
> > I know that A*B = A+B+A:B, but in this case, i.e. doing an adonis2 and
> > specifying by="terms" will only do the test for the interaction, not the
> > main effects. If one chooses by="terms", you will get a test for the main
> > effects and the interaction, but than the order of factors matters.
> >
> > Best regards
> > Ellen
> >
> > On Tue, 16 Oct 2018 at 12:23, Torsten Hauffe < [hidden email]>
> > 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
> >>
> >> On Tue, 16 Oct 2018 at 11:51, Ellen Pape < [hidden email]> wrote:
> >>
> >>> Hi all,
> >>>
> >>> I don't know whether this is the correct mailing group to address this
> >>> question:
> >>>
> >>> I would like to perform a 2way 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]]
> >>>
> >>> _______________________________________________
> >>> Rsigecology mailing list
> >>> [hidden email]
> >>> https://stat.ethz.ch/mailman/listinfo/rsigecology> >>>
> >>
> >
> > [[alternative HTML version deleted]]
> >
> > _______________________________________________
> > Rsigecology mailing list
> > [hidden email]
> > https://stat.ethz.ch/mailman/listinfo/rsigecology>
>
[[alternative HTML version deleted]]
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Rsigecology mailing list
[hidden email]
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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 1e04 ***
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 < [hidden email]> 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 < [hidden email]> wrote:
> >
> >> Hi all,
> >>
> >> I don't know whether this is the correct mailing group to address this
> >> question:
> >>
> >> I would like to perform a 2way 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]]
> >>
> >> _______________________________________________
> >> Rsigecology mailing list
> >> [hidden email]
> >> https://stat.ethz.ch/mailman/listinfo/rsigecology> >>
> >
> > [[alternative HTML version deleted]]
> >
> > _______________________________________________
> > Rsigecology mailing list
> > [hidden email]
> > https://stat.ethz.ch/mailman/listinfo/rsigecology> >
> _______________________________________________
> Rsigecology mailing list
> [hidden email]
> https://stat.ethz.ch/mailman/listinfo/rsigecology>
[[alternative HTML version deleted]]
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Rsigecology mailing list
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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 < [hidden email]> 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 1e04 ***
> 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 < [hidden email]> 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 < [hidden email]> wrote:
>>>
>>>> Hi all,
>>>>
>>>> I don't know whether this is the correct mailing group to address this
>>>> question:
>>>>
>>>> I would like to perform a 2way 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]]
>>>>
>>>> _______________________________________________
>>>> Rsigecology mailing list
>>>> [hidden email]
>>>> https://stat.ethz.ch/mailman/listinfo/rsigecology>>>>
>>>
>>> [[alternative HTML version deleted]]
>>>
>>> _______________________________________________
>>> Rsigecology mailing list
>>> [hidden email]
>>> https://stat.ethz.ch/mailman/listinfo/rsigecology>>>
>> _______________________________________________
>> Rsigecology mailing list
>> [hidden email]
>> https://stat.ethz.ch/mailman/listinfo/rsigecology>>
>
> [[alternative HTML version deleted]]
>
> _______________________________________________
> Rsigecology mailing list
> [hidden email]
> https://stat.ethz.ch/mailman/listinfo/rsigecology_______________________________________________
Rsigecology mailing list
[hidden email]
https://stat.ethz.ch/mailman/listinfo/rsigecology


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 pvalue 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 < [hidden email]> 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 <
> [hidden email]> 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 1e04 ***
> > 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 < [hidden email]> 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 < [hidden email]> wrote:
> >>>
> >>>> Hi all,
> >>>>
> >>>> I don't know whether this is the correct mailing group to address this
> >>>> question:
> >>>>
> >>>> I would like to perform a 2way 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]]
> >>>>
> >>>> _______________________________________________
> >>>> Rsigecology mailing list
> >>>> [hidden email]
> >>>> https://stat.ethz.ch/mailman/listinfo/rsigecology> >>>>
> >>>
> >>> [[alternative HTML version deleted]]
> >>>
> >>> _______________________________________________
> >>> Rsigecology mailing list
> >>> [hidden email]
> >>> https://stat.ethz.ch/mailman/listinfo/rsigecology> >>>
> >> _______________________________________________
> >> Rsigecology mailing list
> >> [hidden email]
> >> https://stat.ethz.ch/mailman/listinfo/rsigecology> >>
> >
> > [[alternative HTML version deleted]]
> >
> > _______________________________________________
> > Rsigecology mailing list
> > [hidden email]
> > https://stat.ethz.ch/mailman/listinfo/rsigecology>
>

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) 8446966
Email: [hidden email]
* Do not print this email unless you really need to. Save paper and
protect the environment! *
[[alternative HTML version deleted]]
_______________________________________________
Rsigecology mailing list
[hidden email]
https://stat.ethz.ch/mailman/listinfo/rsigecology


Gian,
I am bit confused by what your concern is. First, if the imbalance is not that severe, the approach you take to analyzing a twoway permanova (type I, type II, type III ss) is not going to matter that much. Indeed, if the design were balanced, they would give you identical results. Second, regardless of the lack of balance, for the models y ~ A + B + A:B and y ~ B + A + A:B, the test for the interaction will be the same. So, I don’t understand why you would want to drop the main effects from the model, effectively combining them with interaction. That doesn’t make any sense to me. The problem is with the tests of the main effects.
My advice is to run both models (i.e., A first, then B first) using type I ss. As mentioned, both models will give you the same interaction result. If the interaction is all that you’re interested in, problem solved. Interpret only the interaction and and ignore the main effects. If the interaction is not significant and low, then interpret only the main effects, focusing only on the second main effect in each of the differentlyordered models (which are equivalent to Type II ss tests). And these results will tell you pretty the same thing as type III tests if there is little or no interaction. I would not worry about trying to estimate the main effects while controlling for the interaction (Ellen’s question), which cannot be done using type I or type II SS in 2way permanova using adonis. But why would you want to? The lack of a balanced design results in the main effects and the interaction not being independent of one another. Forcing that independence by using type III ss can only work by essentially "throwing away" some of the information associated with the main effects, possibly resulting in an overly conservative test. The lower the interaction, however, the less is thrown away and the less it matters.
Steve
Stephen Brewer
[hidden email]<mailto: [hidden email]>
Professor
Department of Biology
PO Box 1848
University of Mississippi
University, Mississippi 386771848
Brewer web page  https://jstephenbrewer.wordpress.comFAX  6629155144 Phone  6622025877
On Oct 31, 2018, at 5:45 PM, Gian Maria Niccolò Benucci < [hidden email]<mailto: [hidden email]>> wrote:
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 pvalue 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 < [hidden email]<mailto: [hidden email]>> 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 <
[hidden email]<mailto: [hidden email]>> 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 1e04 ***
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 < [hidden email]<mailto: [hidden email]>> 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 < [hidden email]<mailto: [hidden email]>> wrote:
Hi all,
I don't know whether this is the correct mailing group to address this
question:
I would like to perform a 2way 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]]
_______________________________________________
Rsigecology mailing list
[hidden email]<mailto: [hidden email]>
https://stat.ethz.ch/mailman/listinfo/rsigecology [[alternative HTML version deleted]]
_______________________________________________
Rsigecology mailing list
[hidden email]<mailto: [hidden email]>
https://stat.ethz.ch/mailman/listinfo/rsigecology_______________________________________________
Rsigecology mailing list
[hidden email]<mailto: [hidden email]>
https://stat.ethz.ch/mailman/listinfo/rsigecology [[alternative HTML version deleted]]
_______________________________________________
Rsigecology mailing list
[hidden email]<mailto: [hidden email]>
https://stat.ethz.ch/mailman/listinfo/rsigecology
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) 8446966
Email: [hidden email]<mailto: [hidden email]>
* Do not print this email unless you really need to. Save paper and
protect the environment! *
[[alternative HTML version deleted]]
_______________________________________________
Rsigecology mailing list
[hidden email]<mailto: [hidden email]>
https://stat.ethz.ch/mailman/listinfo/rsigecology [[alternative HTML version deleted]]
_______________________________________________
Rsigecology mailing list
[hidden email]
https://stat.ethz.ch/mailman/listinfo/rsigecology


Thank you very much Steve,
I really appreciate you answer. I do not want to drop the main effects out
form the model, I was just trying to understand how adonis works. I was
more confused on how to use the adonis function correctly rather than on
the theory that is behind it. I have an almost "fully crossed" design (that
was the plan, the fact is that I have to remove 2 samples because of the
poor sequencing results) with two factors "Growhouse" and "Stage" in this
case. I am of course interested in the effect of the main factors, but I
also wanted to see if there was a significant interaction and if my
developmental stage (i.e. mature or young) was influenced by where my
organism where growing (i.e. growhouse 1 or 2).
Iif I do as you said, Type I SS for ~ A + B + A*B depends on order so... it
is sequential SS(A) SS(BA) SS(A*BA B)
The interaction is not significant, so maybe worth in this case perform a
Type II test directly?
> adonis(t(otu_fungi_out) ~ Stage + Growhouse + Stage : Growhouse,
data=metadata_fungi_out, permutations=9999)
Call:
adonis(formula = t(otu_fungi_out) ~ Stage + Growhouse +
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 0.0238 *
Growhouse 1 0.3765 0.37647 2.0889 0.08034 0.0561 .
Stage:Growhouse 1 0.2171 0.21708 1.2045 0.04633 0.2376
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
> adonis(t(otu_fungi_out) ~ Growhouse + Stage + Stage : Growhouse,
data=metadata_fungi_out, permutations=9999)
Call:
adonis(formula = t(otu_fungi_out) ~ Growhouse + Stage +
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)
Growhouse 1 0.3765 0.37647 2.0889 0.08034 0.0563 .
Stage 1 0.4877 0.48769 2.7060 0.10408 0.0271 *
Growhouse:Stage 1 0.2171 0.21708 1.2045 0.04633 0.2364
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 Thu, 1 Nov 2018 at 11:06, Steve Brewer < [hidden email]> wrote:
> Gian,
>
> I am bit confused by what your concern is. First, if the imbalance is not
> that severe, the approach you take to analyzing a twoway permanova (type
> I, type II, type III ss) is not going to matter that much. Indeed, if the
> design were balanced, they would give you identical results. Second,
> regardless of the lack of balance, for the models y ~ A + B + A:B and y ~
> B + A + A:B, the test for the interaction will be the same. So, I don’t
> understand why you would want to drop the main effects from the model,
> effectively combining them with interaction. That doesn’t make any sense to
> me. The problem is with the tests of the main effects.
>
> My advice is to run both models (i.e., A first, then B first) using type I
> ss. As mentioned, both models will give you the same interaction result. If
> the interaction is all that you’re interested in, problem solved. Interpret
> only the interaction and and ignore the main effects. If the interaction is
> not significant and low, then interpret only the main effects, focusing
> only on the second main effect in each of the differentlyordered models
> (which are equivalent to Type II ss tests). And these results will tell you
> pretty the same thing as type III tests if there is little or no
> interaction. I would not worry about trying to estimate the main effects
> while controlling for the interaction (Ellen’s question), which cannot be
> done using type I or type II SS in 2way permanova using adonis. But why
> would you want to? The lack of a balanced design results in the main
> effects and the interaction not being independent of one another. Forcing
> that independence by using type III ss can only work by essentially
> "throwing away" some of the information associated with the main effects,
> possibly resulting in an overly conservative test. The lower the
> interaction, however, the less is thrown away and the less it matters.
>
>
> Steve
>
>
>
>
> Stephen Brewer
> [hidden email]
> Professor
> Department of Biology
> PO Box 1848
> University of Mississippi
> University, Mississippi 386771848
> Brewer web page  https://jstephenbrewer.wordpress.com> FAX  6629155144 Phone  6622025877
>
>
>
>
>
> On Oct 31, 2018, at 5:45 PM, Gian Maria Niccolò Benucci <
> [hidden email]> wrote:
>
> 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 pvalue 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 < [hidden email]> 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 <
>
> [hidden email]> 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 1e04 ***
> 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 < [hidden email]> 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 < [hidden email]> wrote:
>
> Hi all,
>
> I don't know whether this is the correct mailing group to address this
> question:
>
> I would like to perform a 2way 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
>
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