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After doing a PCA using princomp, how do you view how much each component contributes to variance in the dataset. I'm still quite new to the theory of PCA - I have a little idea about eigenvectors and eigenvalues (these determine the variance explained?). Are the eigenvalues related to loadings in R? Thanks, Paul -- View this message in context:

Hi, Am wanting to save the summary of a PCA to file. Have tried: > write.table(summary(PCA), file="PCAvar.txt", sep="\t") but receive: Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors) : cannot coerce class "summary.princomp" into a data.frame What am I doing wrong? Thanks -- View this message in context:

Hi, I'm wanting to do a PCA on some data which is comprised of two different groups (to see how well the groups are discriminated). Is there a way to change the colour of the datapoints in a biplot so that I can easily see which group is which (eg objects 1-100, red, 101-200, black). Might be simple, but I'm new to R and can't seem to find how to do this. Thanks. Paul -- View this

Hi, I'm wanting to test for a difference in medians between 2 groups using resampling methods. I found the boot package, but don't really understand how to write the 'statistic' function required as the 2nd argument for the bootstrap test. Thanks if you can help, Paul -- View this message in context: http://www.nabble.com/Help-with-%27boot%27-tp22653487p22653487.html Sent from

Hi, I'm learning to write some basic functions in R. For some data I have I'd like to be able to add a variable to itself after each iteration in a for loop to obtain a grandtotal for that variable so I can calculate a mean. test<-function(data){ for (i in 1:80){ meanrotation<-(abs(data[i,3]-data[i,2])+abs(data[i,4]-data[i,2])+abs(data[i,5]-data[i,2])+abs(data[i,6]-data[i,2]))/4

This is no doubt a very basic question for most R users, but is there an easy way to reorder the variables (columns) in a dataframe (I can't seem to find an answer anywhere). I've generally been creating a new dataframe and selecting the new order I want from the old but this is time-consuming. Thanks, Paul -- View this message in context:

Hi, I'm wanting to exclude data more than 2 sd's from the mean before proceeding with further analyses. I've created new logical variables (a and b) and written them to the existing dataframe. I want to be able to subset the TRUE observations based on another 2 factor variable. I'm assuming this is possible, but I don't know what I'm doing wrong, as I get results that

Hi, I'm very new to R. I want to know if there is any way to write only the lower half of a distance matrix created in R to a csv file for example. I get the 'cannot coerce class "dist" into a data.frame' message when I try. I have used as.matrix and can write to a file this way, but as a full matrix. The reason I only want the lower half is that I've been doing some

Hi, I've performed an lda and obtained a classification table for some of my data: > efa.dfa<-lda(groups~.,efa.scores.8,CV=T) > str(efa.dfa) List of 5 $ class : Factor w/ 2 levels "1","2": 1 2 1 2 1 1 2 2 1 2 ... $ posterior: num [1:160, 1:2] 0.99083 0.00852 0.93983 0.23186 0.85931 ... ..- attr(*, "dimnames")=List of 2 .. ..$ : chr [1:160]

Hi, Am newish to stats and R, so I certainly appreciate any help. Basically I have 50 inidividuals whom I have 6 photos each of their optic nerve head. I want to check that the orientation of the nerve head is consistent, ie the 6 replicates show minimal or preferably no rotation differences. I'll draw an arbitrary line between some blood vessels (same reference in each set of replicates) and

Hi, I've got 4 variables that I want to effectively 'stack' so that I have a grand R variable and a grand L variable. This works to achieve that goal: Twin1cor<-with(twin.wide,cbind(ACDepthR.1,ACDepthL.1)) Twin2cor<-with(twin.wide,cbind(ACDepthR.2,ACDepthL.2)) Both<-rbind(Twin1cor,Twin2cor) > str(Both) num [1:1858, 1:2] 3.36 NA NA NA NA NA NA 3.92 3.5 NA ... - attr(*,

Hi, I'm essentially wanting to calculate intra- and inter-observer variabilities for the first principal component of an optic disc shape measure of a sample of individuals, so from what I can work out I need to work out an intraclass correlation coefficient(s). For the intra-data, I have 2 measurements taken on each individual by the same observer. For the inter-data, 2 observers have taken

Hi, I thought I'd like to try out JGR, but after installing the package (and dependencies) I receive the following when I try to load it: > library(JGR) Loading required package: rJava Loading required package: JavaGD Loading required package: iplots Note: On Mac OS X we strongly recommend using iplots from within JGR. Proceed at your own risk as iplots cannot resolve potential ev.loop