From: Oyomoare Osazuwa-Peters <oyomo...@yahoo.com> Subject: Re: [R] Help! To: "Erich Neuwirth" <erich.neuwi...@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.neuwi...@univie.ac.at> wrote: From: Erich Neuwirth <erich.neuwi...@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, à species, individual and core (i.e. 20 species, at least 6 > individuals > of each species, and 2 cores from each individual). à 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 ââ¬Ëaââ¬â¢ of individual 1 in > the species ââ¬ÅApeimeââ¬ï¿½. 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. > > Ã > > Code: > > Ã > > 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) > > Ã > > Thanks > > Ã > > Oyomoare > > > > >     >    [[alternative HTML version deleted]] > > > > > ______________________________________________ > 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. -----Inline Attachment Follows----- ______________________________________________ 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. [[alternative HTML version deleted]]
______________________________________________ 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.
