[R-sig-ME] [R] Fwd: Re: ANOVA and Pseudoreplication in R

Robert A LaBudde ral at lcfltd.com
Sun Feb 27 06:46:22 CET 2011

I think you are over-concerned with the term "pseudo-replication". 
All this means is that the error source is nested, and not a full replicate.

What you haven't done, and need to do, is to describe your experiment 
in terms of the real variables and error sources. Then code them as 
"fixed" or "random" and write the model form.

You description is very complex and confusing. You need to identify:

1. Exactly what culture is used in each trial.
2. All subcultures: NE vs EV, which chemical, etc.
3. Which plate.
4. Which circle on which plate.
5. Which measurement on which circle.

After you have identified all descriptors that identify each 
individual measurement, put them in a file with columns for factors 
and the outcome.

At this point it should be clear that you have a number of random 
factors: plate, circle, measurement, plus any culture replicates, if 
you have them.

One you successfully do this, you can write the model equation with 
the proper nesting.

The time to do all this is BEFORE you conduct the experiment.

At 10:44 AM 2/26/2011, Ben Ward wrote:
>On 25/02/2011 21:22, Ben Ward wrote:
>>-------- Original Message --------
>>Subject:        Re: [R] ANOVA and Pseudoreplication in R
>>Date:   Fri, 25 Feb 2011 12:10:14 -0800
>>From:   Bert Gunter<gunter.berton at gene.com>
>>To:     Ben Ward<benjamin.ward at bathspa.org>
>>CC:     r-help<r-help at r-project.org>
>>I can hopefully save bandwidth here by suggesting that this belongs on
>>the R-sig-mixed-models list.
>>-- Bert
>>As an aside, shouldn't you be figuring this out yourself or seeking 
>>local consulting expertise?
>I did consult with the lecturer at university that knows most about 
>stats, and he advised me:
>"Pseudo replication is really about a lack of independence between 
>measurements, So you need to work backwards and see where you are 
>building in a known lack of independence.  And where that is the 
>case you need to use means of all the values."
>And I have done this and came to the conclusion I mentioned as to 
>where I thought Pseudoreplicaton was comming from, however, I do not 
>know about the one other 'potential' source as it really is for me 
>at least, a grey area.
>I've consulted a few forums that deal with the theory more and await 
>any response. Until then I'll have to try and get as many opinions 
>on it as possible.
>-Ben W.
>>On Fri, Feb 25, 2011 at 9:08 AM, Ben Ward<benjamin.ward at bathspa.org>   wrote:
>>>   Hi, As part of my dissertation, I'm going to be doing an Anova, comparing
>>>   the "dead zone" diameters on plates of microbial growth with little paper
>>>   disks "loaded" with antimicrobial, a clear zone appears where 
>>> death occurs,
>>>   the size depending on the strength and succeptibility. So it's 
>>> basically 4
>>>   different treatments, and I'm comparing the diameters (in mm) of circles.
>>>   I'm concerned however, about Pseudoreplication and how to deal 
>>> with it in R,
>>>   (I thought of using the Error() term.
>>>   I have four levels of one factor(called "Treatment"): 
>>> NE.Dettol, EV.Dettol,
>>>   NE.Garlic, EV.Garlic.   ("NE.Dettol" is E.coli not evolved to dettol,
>>>   exposed to dettol to get "dead zones". And the same for 
>>> NE.Garlic, but with
>>>   garlic, not dettol. "EV.Dettol" is E.coli that has been evolved against
>>>   dettol, and then tested afterwards against dettol to get the 
>>> "dead zones".
>>>   Same applies for "EV.Garlic" but with garlic).  You see from 
>>> the four levels
>>>   (or treatments) there are two chemicals involved. So my first concern is
>>>   whether they should be analysed using two seperate ANOVA's.
>>>   NE.Dettol and NE.Garlic are both the same organism - a lab stock E.coli,
>>>   just exposed to two different chemicals.
>>>   EV.Dettol and EV.Garlic, are in principle, likely to be two 
>>> different forms
>>>   of the organism after the many experimental doses of their respective
>>>   chemical.
>>>   For NE.Garlic and NE.Dettol I have 5, what I've called 
>>> "Lineages", basically
>>>   seperate bottles of them (10 in total).
>>>   Then I have 5 Bottles (Lineages) of EV.Dettol, and 5 of EV.Garlic. - This
>>>   was done because there was the possiblity that, whilst I'm expecting them
>>>   all to respond in a similar manner, there are many evolutionary 
>>> paths to the
>>>   same result, and previous research and reading shows that 
>>> occasionally one
>>>   or two react differently to the rest through random chance.
>>>   The point I observed above ("NE.Dettol and NE.Garlic are both the same
>>>   organism...") is also applicable to the 5 bottles: The 5 bottles each of
>>>   NE.Garlic and NE.Dettol are supposed to be all the same organism - from a
>>>   stock one kept in store in the lab.
>>>   There is potential though for the 5 of EV.Garlic, to be 
>>> different from one
>>>   another, and potential for the 5 EV.Dettol to be different from 
>>> one another.
>>>   The Lineage (bottle) is also a factor then, with 5 levels (1,2,3,4,5).
>>>   Because they may be different.
>>>   To get the measurements of the diamter of the zones. I take out a small
>>>   amount from a tube and spread it on a plate, then take three paper disks,
>>>   soaked in their respective chemical, either Dettol or Garlic. 
>>> and press them
>>>   and and incubate them.
>>>   Then when the zones have appeared after a day or 2. I take 4 diameter
>>>   measurements from each zone, across the zone at different angles, to take
>>>   account for the fact, that there may be a weird shape, or not quite
>>>   circular.
>>>   I'm concerned about pseudoreplication, such as the multiple readings from
>>>   one disk, and the 5 lineages - which might be different from 
>>> one another in
>>>   each of the Two "EV." treatments, but not with "NE." treatments.
>>>   I read that I can remove pseudoreplication from  the multiple 
>>> readings from
>>>   each disk, by using the 4 readings on each disk, to produce a 
>>> mean for the
>>>   disks, and analyse those means - Exerciseing caution where 
>>> there are extreme
>>>   values. I think the 3 disks for each lineage themselves are not
>>>   pseudoreplication, because they are genuinley 3 disks on a 
>>> plate: the "Disk
>>>   Diffusion Test" replicated 3 times - but the multiple readings 
>>> from one disk
>>>   if eel, is pseudoreplication. I've also read about including 
>>> Error() terms
>>>   in a formula.
>>>   I'm unsure of the two NE. Treatments comming from the same 
>>> culture does not
>>>   introduce pseudoreplications at Treatment Factor Level, because 
>>> of the two
>>>   different antimicrobials used have two different effects.
>>>   I was hoping for a more expert opinion on whether I have identified
>>>   pseudoreplication correctly or if there is indeed 
>>> pseudoreplication in the 5
>>>   Lineages or anywhere else I haven't seen. And how best this is 
>>> dealt with in
>>>   R. At the minute my solution to the multiple readings from one disk is to
>>>   simply make a new factor, with the means on and do Anova from 
>>> that, or even
>>>   take the means before I even load the dataset into R. I'm wondering if an
>>>   Error() term would be correct.
>>>   Thanks,
>>>   Ben W.
>>>   ______________________________________________
>>>   R-help at r-project.org mailing list
>>>   https://stat.ethz.ch/mailman/listinfo/r-help
>>>   PLEASE do read the posting guide 
>>> http://www.R-project.org/posting-guide.html
>>>   and provide commented, minimal, self-contained, reproducible code.
>R-help at r-project.org mailing list
>PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>and provide commented, minimal, self-contained, reproducible code.

Robert A. LaBudde, PhD, PAS, Dpl. ACAFS  e-mail: ral at lcfltd.com
Least Cost Formulations, Ltd.            URL: http://lcfltd.com/
824 Timberlake Drive                     Tel: 757-467-0954
Virginia Beach, VA 23464-3239            Fax: 757-467-2947

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