Okay, thank you.
On Mon, Dec 5, 2011 at 12:01 AM, Bert Gunter <gunter.ber...@gene.com> wrote:
> The concentrations of the different metals within an animal are
> correlated, so that doing as you suggest will almost certainly result
> in nonsense P values. So I suggest you seek local statistical help or,
> failing that, post on a statistical forum like stats.stackexchange.com
> .
>
> There are various multivariate packages -- check e.g. the ChemPhys
> and Multivariate task views -- that may be pertinent, but your post
> suggests that you probably need some help to use them. Ergo my
> suggestion above.
>
> Cheers,
> Bert
>
> On Sun, Dec 4, 2011 at 7:36 AM, Kaiyin Zhong <kindlych...@gmail.com> wrote:
>> I have assayed the concentrations of various metal elements in
>> different anatomic regions of two strains of mice. Now, for each
>> element, in each region, I want to do a t test to find whether there
>> is any difference between the two strains.
>>
>> Here is what I did (using simulated data as an example):
>>
>> # create the data frame
>>> elemconc = data.frame(expand.grid(id=1:3, geno=c('exp', 'wt'),
>>> region=c('brain', 'spine'), elem=c('fe', 'cu', 'zn')), conc=rnorm(36, 10))
>>> elemconc
>> id geno region elem conc
>> 1 1 exp brain fe 8.497498
>> 2 2 exp brain fe 9.280944
>> 3 3 exp brain fe 9.726271
>> 4 1 wt brain fe 11.556397
>> 5 2 wt brain fe 10.992550
>> 6 3 wt brain fe 9.711200
>> 7 1 exp spine fe 11.168603
>> 8 2 exp spine fe 9.331127
>> 9 3 exp spine fe 11.048226
>> 10 1 wt spine fe 8.480867
>> 11 2 wt spine fe 8.887062
>> 12 3 wt spine fe 8.329797
>> 13 1 exp brain cu 10.242652
>> 14 2 exp brain cu 9.865984
>> 15 3 exp brain cu 9.163728
>> 16 1 wt brain cu 11.099385
>> 17 2 wt brain cu 9.364261
>> 18 3 wt brain cu 9.718322
>> 19 1 exp spine cu 10.720157
>> 20 2 exp spine cu 11.505430
>> 21 3 exp spine cu 9.499359
>> 22 1 wt spine cu 9.855950
>> 23 2 wt spine cu 10.120489
>> 24 3 wt spine cu 9.526252
>> 25 1 exp brain zn 9.736196
>> 26 2 exp brain zn 11.938710
>> 27 3 exp brain zn 9.668625
>> 28 1 wt brain zn 9.961574
>> 29 2 wt brain zn 10.461621
>> 30 3 wt brain zn 9.873667
>> 31 1 exp spine zn 9.708067
>> 32 2 exp spine zn 10.109309
>> 33 3 exp spine zn 10.973387
>> 34 1 wt spine zn 8.406536
>> 35 2 wt spine zn 7.797746
>> 36 3 wt spine zn 11.127984
>>
>> # use tapply to aggregate
>>> tapply(elemconc$conc, elemconc[c('elem', 'region')], function(x) x)
>> region
>> elem brain spine
>> fe Numeric,6 Numeric,6
>> cu Numeric,6 Numeric,6
>> zn Numeric,6 Numeric,6
>>
>> # check whether the order of data has been preserved after aggregation
>>> x['fe', 'brain']
>> [[1]]
>> [1] 8.497498 9.280944 9.726271 11.556397 10.992550 9.711200
>>
>> # create an external factor for strain grouping
>>> tmpgeno = rep(c('exp', 'wt'), each=3)
>>> tmpgeno
>> [1] "exp" "exp" "exp" "wt" "wt" "wt"
>>
>> # do the t test using the grouping factor
>>> x = tapply(elemconc$conc, elemconc[c('elem', 'region')], function(x)
>>> t.test(x~tmpgeno) )
>>> x
>> region
>> elem brain spine
>> fe List,9 List,9
>> cu List,9 List,9
>> zn List,9 List,9
>>
>> I believe I have made no mistakes so far, but I wonder is there a
>> better way of doing this?
>>
>>
>> --
>> Kaiyin Zhong
>> ------------------------------------------------------------------------------------------------------------------
>> Neuroscience Research Institute, Peking University, Beijing, P.R.China 100038
>>
>> ______________________________________________
>> 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
>
> Internal Contact Info:
> Phone: 467-7374
> Website:
> http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm
--
Kaiyin Zhong
------------------------------------------------------------------------------------------------------------------
Neuroscience Research Institute, Peking University, Beijing, P.R.China 100038
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