[R-sig-eco] Help with model selection

[Altaf Hussain]

 Thank you for your reply, Bob! MONOVA was one of the options on my list,
till I realized that it actually compares one or more categorical
independent variable(s) with two or more treatment levels AND more than one
continuous response variable (chemicals in my case). I don't know where to
accommodate my explanatory variables (i.e., soil nutrients) in a MANOVA. As
far as I understand it, MANOVA is more suitable when you have discrete
groups, I have both. All of my response and explanatory variables are
continuous variables. Would you recommend adonis PERMANOVA, ANOSIM or MRPP?
I did book an appointment with the UoA statistics department, thank you for
pointing to it.

I really appreciate the time you’ve taken out of your schedule to help me
out.

-Simon

On Fri, Mar 16, 2018 at 3:04 AM, Bob OHara <bob.ohara at ntnu.no> wrote:

> The design is good. But the details will matter. I think the best advice I
> can offer is to seek advice! Your university has a consulting service:
> http://www.stat.ualberta.ca/~tcc/#home, and I think half an hour with
> them looking at your data with you will help a lot.
>
> You have a multivariate response, so a MANOVA is probably needed. The full
> (horrible) model you have is
>
> Time*Treatment*Moisture/Site/Tree
>
> where Time is before/after, and Treatment is the inoculation. Hopefully
> you can remove some of the interactions: the Time*Treatment*Moisture terms
> are important, so you would hope that the interactions with Tree and Site
> don't matter.
>
> Tree should probably be a random effect, although it is less important her
> because your design is good.
>
> I think giving more advice than this would require some poking around the
> data, but I hope this is a help.
>
> Bob
>
> On 03/16/2018 03:33 AM, Altaf Hussain wrote:
>
>> Hello everyone,
>>
>> I have some field collected data from *90* random trees on *6* sites and
>> I am comparing the trees for the concentrations of different chemical
>> compounds. The chemicals are of two different types, *(Group 1 = A, B, C,
>> D, E, F and their sum, X)* & *(Group 2 = G, H, I, J and their sum, Y)*. I
>> also have the sum of X and Y that I call Z. All variables are continuous
>> and use the same units. The 6 sites are closely located but are unique in
>> terms of their soil nutrients (N, P K, S and their sum, Tot.Nutrients,
>> *continuous/same
>> units*) and soil moisture. I further grouped the sites for soil moisture
>> and I now have 2 Dry, 2 Medium dry and 2 Wet sites, (6/3=2), character
>> variables. Each site has 15 trees and an equal number of trees i.e., (5)
>> were treated using different fungal inoculation densities i.e., (0 for
>> control, 4 and 16).  The trees were sampled in a pre and post inoculation
>> manner, where the pre inoculation samples serve to determine the baseline
>> chemistry of trees and the post inoculation samples will show the chemical
>> responses of the trees to inoculations *(if any!).*
>>
>> Alright, first thing first, I admit that I am very new to statistical
>> modeling, which is why I have such a complicated design, and which is why
>> I
>> am posting ☺.  The following are the questions that I want to answer using
>> my dataset introduced above:
>>
>> 1) How do I compare my 6 sites for trees' chemical responses to the
>> different inoculation densities?
>> 2) How do I check if any of the nutrients, their interaction, or their
>> interaction with soil moisture is playing a role in the chemical
>> variation?
>>
>> I am open to any suggestions that will improve my study!
>>
>> I am using RStudio version 3.4.3 for the analysis.
>>
>> I appreciate any input that will help me with the analysis.
>>
>> Regards,
>>
>> //Simon
>>
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>>
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>
> --
> Bob O'Hara
> Institutt for matematiske fag
> NTNU
> 7491 Trondheim
> Norway
>
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