[R] ANOVA problem

[rob.griffin.247]

Gee Bert, thanks for the really helpful tip. But if you read my post properly
you'll note that I do know how ANOVA's work. 
> The anova of *G* /AB01 /would be some thing like: y=V, fixed=S, Random= L
> &
> L*S...

I didn't want to show a full model formula in case it led people do the
wrong path to solving the real problem (seeing as there are several ways to
create mixed effects models which for some reason may not work with
solutions to the problem) which is how to actually get R to do ANOVA to
analyse the data for each value of G in the data frame given in the example
and then get R to give me the output data frame I desire, ergo, *it is
indeed an R problem.*

Perhaps you should read up on the R mailing list posting guidelines:
"Questions about statistics: The R mailing lists are primarily intended for
questions and discussion about the R software. However, questions about
statistical methodology are sometimes posted. If the question is well-asked
and of interest to someone on the list, *it may elicit an informative
up-to-date answer....*"  so not rude and sarcastic ones then..

I will admit statistics is an element of the question I have posed, but it
is entirely in an R based context.
My understanding of statistics is perfectly acceptable thanks to numerous
courses taken through my undergraduate, masters, and PhD studies. If you're
not willing to help someone solve their problems then don't bother posting -
do you have nothing better to do with your time?

I would also suggest that my post has a lot more to do with R than your post
just moments ago which is solely about statistics and is of no relevance to
the R help forum. 
http://r.789695.n4.nabble.com/Off-Topic-Crime-Statistics-Don-t-Pay-td4609170.html
http://r.789695.n4.nabble.com/Off-Topic-Crime-Statistics-Don-t-Pay-td4609170.html 

I know you regularly post on this forum and are often helpful, but sometimes
unhelpful posts are unnecessary. 

Rant over. 

As for everyone else:
Firstly, sorry about the above, it's been a long week. Secondly, I would
still really like some helpful answers from people who are interested in
helping me, and more constructive replies will be greatly appreciated.

On Fri, May 4, 2012 at 9:18 AM, robgriffin247 <rg.rforum at .co> wrote:
> Hi,
> I need to create a data frame containing the results of a number of
> ANOVA's
> but I'm having some trouble setting it up (some being enough for me to
> spend
> 3 days trying with no progress and be left staring in to the abyss which
> some people call a weekend, and what I will call 2 quiet days in the
> office...)

I would suggest staying out of the office and consulting a local
statistician Monday morning. As a poor second choice, post on a
statistics Help list (e.g. stats.stackexchange.com).

I haven't gone through your post in detail, but it appears to have
little to do with R and a **lot** to do with your lack of statistical
understanding. It appears that you need to formulate a scientifically
appropriate mixed effect model (the problem is never "how to set up an
anova"), and interaction with a local consultant is the best way to do
that.

I suppose you could also post this on the r-sig-mixed-models list, as
they often go beyond the R issues to the statistical modeling. But
remote consulting is a risky business, as despite the best of
intentions on both sides, incomplete or mis- communication can lead to
errors of the third kind (right answer -- wrong question).

Best,
Bert

>
> The response variable is *V*.
> I need to do an ANOVA for each *G*.
> The fixed effect will be *S* ("M" or "F") whilst also having the *S*L* and
> *L* ("1" or "2") as random effects.
> The anova of *G* /AB01 /would be some thing like: y=V, fixed=S, Random= L
> &
> L*S...
> The new data frame would then compile all the variance components for each
> G, including total and residual variance.
>
> here is the example dataframe using 2 G's, with 2 S values, 2 L, and 2
> replicates for each.
>
> df<-as.data.frame(c("AB01","AB01","AB01","AB01","AB01","AB01","AB01","AB01","AB02","AB02","AB02","AB02","AB02","AB02","AB02","AB02"))
> names(df)<-"G"
> df$L<-as.numeric(c(1,1,1,1,2,2,2,2,1,1,1,1,2,2,2,2))
> df$S<-(c("m","m","f","f","m","m","f","f","m","m","f","f","m","m","f","f"))
> df$R<-as.numeric(c(1,2,1,2,1,2,1,2,1,2,1,2,1,2,1,2))
> df$V<-as.numeric(c(1,2,12,21,5,6,12,34,1,6,52,41,5,43,13,24))
>
> It is worth noting the actual data this will be used on is >10000*G's,
> 2*S's,  40*L's,  and 2*R's so hand writing an ANOVA for each G is not
> preferred...
>
> Here is a twitter link to a crudely drawn illustration of the aim
> illustrated (using 3 Ls) in case I have confused you with words (through
> my
> own poor understanding):
> https://twitter.com/#!/robgriffin247/status/198446041316593666/photo/1/large
> https://twitter.com/#!/robgriffin247/status/198446041316593666/photo/1/large
>
> Thanks in advance for your time,
> Rob
> (please save my weekend...)
>
> --
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>
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-- 

Bert Gunter
Genentech Nonclinical Biostatistics

Internal Contact Info:
Phone: 467-7374
Website:
http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm

______________________________________________
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