Hi Ben: 1) Confession: I did not and have not read your post in detail.
2) IMHO, the following advice: > "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." is baloney. The "lack of independence" part is correct. The baloney part is "take the mean." That is exactly where mixed models -- or hierarchical modeling of some sort -- is required. That's why I referred you to R-sig-mixed-models. Again, please note: IMHO. Maybe I'm the one full of baloney. It's free advice, after all, so beware of what you get. Cheers, Bert On Sat, Feb 26, 2011 at 7:44 AM, Ben Ward <benjamin.w...@bathspa.org> 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.ber...@gene.com> >> To: Ben Ward<benjamin.w...@bathspa.org> >> CC: r-help<r-help@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.w...@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@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. >>> >> >> > > -- Bert Gunter Genentech Nonclinical Biostatistics ______________________________________________ R-help@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.