
From: Oyomoare Osazuwa-Peters <oyomoare@yahoo.com>
Subject: Re: [R] Help!
To: "Erich Neuwirth" <erich.neuwirth@univie.ac.at>
Date: Monday, September 20, 2010, 5:16 PM

Thanks for responding to my request for help.
I understand what you mean about the repeated measurements methods for the two cores. The thing though is to answer my research question, the data I really need is the radial gradient (equals the slope from a regression of the response variable (WD) on the predictor (DP)) for each core. Then, I can be begin to test for the effects of species, individuals and core using an appropriate test (likely nested anova). For now I am in the initial process of getting radial
 gradients and having problems with the code that would instruct R to do it all at once.
My main problem is when I define the subsetting indices to be species, individual and core at the same time for the whole data frame, so that R performs the operation for each of the 240 data subsets automatically, it doesn't work. But it works when I define only a single subset of the data like I showed in my first mail. 

Oyomoare

--- On Mon, 9/20/10, Erich
 Neuwirth <erich.neuwirth@univie.ac.at> wrote:

From: Erich Neuwirth <erich.neuwirth@univie.ac.at>
Subject: Re: [R] Help!
To: r-help@r-project.org
Date: Monday, September 20, 2010, 5:02 PM

If you assume that the variance is the same in all your subsets,
you can do an lm analysis with your subset classification as a factor.
You could also analyze the interaction between factors
and between factors and your numeric independent variable.
You also should consider repeated measurement methods since
you are taking 2 cores from the same individuals.

On 9/20/2010 11:46 PM, Oyomoare Osazuwa-Peters wrote:
> Please I need some help using R to 
> analyze my data. What I
> would like to do is to repeat the same basic process (e.g. linear
 regression
> between
 wood density and distance from pith) for at least 240 data 
> subsets
> within the main data-frame. Within the main data-frame, these data subsets will be defined by three 
> variables
> namely, Â species, individual and core (i.e. 20 species, at least 6 
> individuals
> of each species, and 2 cores from each individual). Â Whereas I can write
> the code to carry out this process for each subset, I am unable to 
> successfully
> instruct R to automatically carry out the process for each of these 
> subsets (perhaps using loops). So to illustrate what I have done so far 
> with the codes
> below I was able to run a regression
>  analysis for core â€˜aâ€™ of individual 1 in
> the species â€œApeimeâ€�. But rather than do this 240 times, I would like to
>  tell R
> to repeat the process automatically using loops or any method that
 
> works.  
> 
>  Â  
> 
> Code: 
> 
>  Â  
> 
> RG2<-BCI[BCI$Species == "APEIME" 
> &
> BCI$Individual == 1 & BCI$Core == "a", ] 
> 
>> plot(x=RG2$DP..cm., 
> y=RG2$WD..g.cm3,
> xlab="Distance from pith cm", main="APEIME1a",
> ylab="Wood density g/cm3") 
> 
>>
> RG2lm<-lm(RG2$WD..g.cm3~RG2$DP..cm.) 
> 
>> summary(RG2lm) 
> 
>  Â  
> 
> Thanks 
> 
>  Â  
> 
> Oyomoare
> 
> 
> 
> 
>       
>     [[alternative HTML version deleted]]
> 
> 
> 
> 
> ______________________________________________
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