[R] Univariate results from MANOVA with Adonis?

[Martina Ozan]

Hi,

I am using function Adonis in Vegan to do MANOVA. My response variable  
is a chemical profile of an insect composed of different chemical  
compounds (=my data columns). My predictors include factors as well as  
continuous variables. My question is: Is it possible to get out from  
adonis, in addition the multivariate result, also univariate results  
per chemical compounds versus each predictor? I would like to be able  
to pick out individual chemical compounds that are of interest from  
the rest (=those significantly associated/correlated with predictors).


thanks in advance
Martina


--
Martina Ozan, PhD researcher
Centre of Excellence in Biological Interactions
Department of Biosciences
PL 65 (Viikinkaari, 1)
FI-00014 Helsinki University
e-mail: martina.ozan (at) helsinki.fi
http://www.helsinki.fi/science/ants

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Re: [R] Nesting fixed factors in lme4 package

[Martina Ozan]

Hi,

thanks. I am indeed interested in the main effects of A and B and their

interaction+ I want to incorporate C (the block or 'repetition' within which

the A and B treatments were applied) as a random variable. So A*B would be

the way, however errors of A and B are different due to different

experimental plot sizes. When doing Anova the correct code should be this: 

summary(aov(ln_response) ~ A*B + Error(rep/A), data=Exp2)

in which case the effect of A is calculated by using error A*rep

and the effect of B and A*B is calculated using pooled error of B*rep and

A*B*rep

This I dont know how to specify in glmer. Maybe 'nesting' is not a right

term to use (?)


  To: r-h...@stat.math.ethz.ch
 From: bbol...@gmail.com
 Date: Fri, 18 Jan 2013 14:07:02 +
 Subject: Re: [R] Nesting fixed factors in lme4 package
 
 Martina Ozan martina_ozan at hotmail.com writes:
 
  Hi, can anyone tell me how to nest two fixed factors using glmer in
  lme4? I have a split-plot design with two fixed factors - A (whole
  plot factor) and B (subplot factor), both with two levels. I want to
  do GLMM as I also want to include different plots as a random
  factor. But I am interested on the effect of A a B and their
  interaction on the response variable. I tried
  this:glmer(response~A*B+(A/B)+(1|C),data=Exp2,family=poisson but it
  gives the same output as if I removed (A/B) all together or used
  (A:B) instead thus the output is the same as:
  glmer(response~A*B+(1|C),data=Exp2,family=poisson anyone can help
  with how I define this nesting, so that data are analysed correctly
  given my split-plot design? thanks, Martina
 
   In general mixed model questions should go to 
 r-sig-mixed-mod...@r-project.org , but this is actually *not*
 specifically a mixed model problem.  If A and B are fixed factors,
 you're typically interested in A*B, which translates to 1+A+B+A:B,
 i.e. intercept; main effects of A and of B; and the interaction.
 The nesting syntax A/B translates to 1 + A + A:B, i.e. no main
 effect of B.  Nesting would typically make more sense in a random-effects
 context where the meaning of B=1 in unit A=1 is different from
 B=1 in unit A=2, i.e. where you don't want or it doesn't make
 sense to estimate a main effect of B across levels of A.
 
   Ben Bolker
 
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[R] Nesting fixed factors in lme4 package

[Martina Ozan]

Hi, can anyone tell me how to nest two fixed factors using glmer in lme4? I 
have a split-plot design with two fixed factors - A (whole plot factor) and B 
(subplot factor), both with two levels. I want to do GLMM as I also want to 
include different plots as a random factor. But I am interested on the effect 
of A a B and their interaction on the response variable. I tried 
this:glmer(response~A*B+(A/B)+(1|C),data=Exp2,family=poisson but it gives the 
same output as if I removed (A/B) all together or used (A:B) instead thus the 
output is the same as: glmer(response~A*B+(1|C),data=Exp2,family=poisson anyone 
can help with how I define this nesting, so that data are analysed correctly 
given my split-plot design? thanks, Martina


 
 
  
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