hello all R experts,
how do I calculate the reliability between the two groups
using the ICCs?
I'll appreciate your reply,
Thanks
Sincerely,
Supreet kaur,
Biomedical research engineer,
Nationwide Childrens Hospital,
Columbus, OH
(614)355-3509
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On Fri, Nov 11, 2011 at 4:41 PM, Supreet kaur <ksupreet6 at gmail.com> wrote:> hello all R experts, > ? ? ? ? ? ? ? ? how do I calculate the reliability between the two groups > using the ICCs?Possibly by using GmeanRel() from the multilevel package. Searching for reliability group ICC at http://www.rseek.org offers several other options, one of which may be more appropriate for your unspecified application. Sarah -- Sarah Goslee http://www.functionaldiversity.org
________________________________________ Supreet kaur [ksupreet6 at gmail.com]> how do I calculate the reliability between the two groups > using the ICCs?Looking for the irr (inter-rater reliability package) might help; as the name suggests, it includes a variety of measures of rater reliability. S Ellison ******************************************************************* This email and any attachments are confidential. Any use...{{dropped:8}}
Hi, I need to make a subset of my species abundance matrix with only species (columns) that have a total abundance(column sum) greater than 0.5 to do ordination in vegan package. I used following code but it is not working. Can you please give me a solution. gl1<- subset(grassland[,5:44], colSums > 0.05, select=2) gl1 is my new matrix ,and grassland[,5:44] is my original matrix. thanks, Dilshan [[alternative HTML version deleted]]
> Hi, > I need to make a subset of my species abundance matrix with only species> (columns) that have a total abundance(column sum) greater than 0.5 to do> ordination in vegan package. I used following code but it is notworking.> Can you please give me a solution. > > gl1<- subset(grassland[,5:44], colSums > 0.05, select=2)Hm. How did you got this code? By grassland[,5:44] you limit subset to only columns 5:44 function colSums does not know what to sum by select=2 you are choosing only column 2. So it is rather weird collection of commands. grassland[, colSums(grassland) > 0.05] selects all columns for which their sum is over 0.05. What you want to do next is up to you. Regards Petr> > gl1 is my new matrix ,and grassland[,5:44] is my original matrix. > > thanks, > Dilshan > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guidehttp://www.R-project.org/posting-guide.html> and provide commented, minimal, self-contained, reproducible code.
Hi, R development team, I am trying to use PCA in labdsv package.I need to build the ordination plot from scratch. I used the following code (which is used in RDA) and I cannot get the species (variable centroids) to the ordination plot, only I can plot sample unit scores.Can somone help me on this. pca.tr1<-pca(pca1,dim=2) plot(pca.tr1$scores, type="n", main="plot") text(pca.tr1$scores, display="species", col="blue", pch=16) Thanks. Dilshan [[alternative HTML version deleted]]
On 21.11.2011 07:17, dilshan benaragama wrote:> Hi, R development team, > > I am trying to use PCA in labdsv package.I need to build the ordination plot from scratch. I used the following code (which is used in RDA) and I cannot get the species (variable centroids) to the ordination plot, only I can plot sample unit scores.Can somone help me on this. > > pca.tr1<-pca(pca1,dim=2) > plot(pca.tr1$scores, type="n", main="plot") > text(pca.tr1$scores, display="species", col="blue", pch=16)I wonder if you read the posting guide. If so, you forgot to follow the advice given there on subject line, reproducibility, clear problem description etc. Uwe Ligges> Thanks. > > Dilshan > [[alternative HTML version deleted]] > > > > > ______________________________________________ > R-help at 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.