similar to: splitting a square symmetric matrix

Hello all, if I have multiple imputed data sets, is there a command or function in R in any package you know of to combine those, I know one common MI approach is rubins rules, is there a way to do this using his rules or others? I know theres ways, like using Amelia from Gary King's website to create the imputed data sets, but how to make them into one or combine them for analysis.

Is there a way to get confidence intervals around an ordered regression like polr() in the MASS package? ------------------------------------------- Joe King, M.A. Ph.D. Student University of Washington - Seattle 206-913-2912 <mailto:jp@joepking.com> jp@joepking.com ------------------------------------------- Ad astra per aspera - "Through hardships to the stars"

Hello, I am running a model with four categories and want predicted probabilities in each category. Now for this example I wont give a counterfactual just the training data is fine but is there anyway to get a confidence interval around the predicted probabilities in each group? I have tried but it gives me probabilities and I have used interval="confidence", level=.095 and then interval

I have a loop that I would like to use to extract the "stddev" for each itteration so I can average the "stddev" for all the runs. It would be helpful to know how to extract the "stddev" for each run from the VarCorr. Thanks MCruns<-1000 sighatlvec<-rep(NA,MCruns) sighatbvec<-rep(NA,MCruns) sighatevec<-rep(NA,MCruns) for(mc in 1:MCruns) {

Hi all, in R I have?Sys.timezone() function to get the current working Time zone. However I want to have a vector to get the list of all available time zones, like say, LETTERS gives me all letters. Is there any function like that? Thanks in advance,

I'm trying to figure out how to write a r function that will calculate the extreme spread of a group of points given their (x,y) coordinates. Extreme Spread is the maximal Euclidean distance between two points in a group ex.spread = max{ sqrt [ (xi-xj)^2 - (yi-yj)^2 ] } for i not equal to j I have 60 levels to apply this to. There is the combination function in the dprep package but

Ok so if I have a function: functest<-function(x){ a<-x+1 b<-x+2 c<-x+3 paste(a) paste(b) paste(c) } Now I know I can do cat(), or return() on one of them but if I was to run the function with any number, how could I create objects to save so I could do, I am wondering if I have more than one object within my function. functest$a

Anyone know how to get p-values for the t-values from the coefficients produced in vglm? Attached is the code and output ? see comment added to output to show where I need p-values + print(paste("********** Using VGAM function gamma2 **********")) + modl2<- vglm(MidPoint~Count,gamma2,data=modl.subset,trace=TRUE,crit="c") + print(coef(modl2,matrix=TRUE))

I wasn't sure about the subject so I am sorry about the vagueness, but if I have a vector of values, how do I get a certain type of vectors to be bold or italics? So let x be a vector from -10 to 10, how would I tell it to bold the x values that are greater than 0? Or like absolute value of 5? Is it possible to do this in like an if else statement? Could I use x<-seq(-10,10,1)

Hi all, I appreciate the help this list has given me before. I have a question which has been perplexing me. I have been working on doing a Bayesian calculating inserting studies sequentially after using a non-informative prior to get a meta-analysis type result. I created a function using three iterations of this, my code is below. I insert prior mean and precision (I add precision manually

I am wanting to plot a 95% confidence band using segplot, yet I am wanting to have groups. For example if I have males and females, and then I have them in different races, I want the racial groups in different panels. I have this minor code, completely made up but gets at what I am wanting, 4 random samples and 4 samples of confidence, I know how to get A & B into one panel and C&D in to

Hi all, I am trying to run a two factor anova, but one of the factors is a random factor, now I am also running in SPSS and it seems its dividing by the wrong term to get the appropriate F term. here is my data. In SPSS the F scores about double the ones in R, how can I specify one of my factors as a random factor or change it to where it does the right model fitting? I am using the lm command

I am attempting to use rsync to backup a Win98 laptop to a FreeBSD 4.8 backup server. I have experienced the same problem at roughly the same point in the process on two occations. The laptop contains ~2.7Gb of data. On the first attempt we received this error at 2.3Gb and on the second at 2.4Gb. rsync error: partial transfer (code 23) at main.c(575) Would love to have a full backup of the

One thing that's bugged me is that some of the man page lines in the options summary are longer than 79 chars and wrap onto the next line. These are just one line summaries (detailed description appear later) so they can, and should, be terse. Here's an edited diff showing my proposed changes (and a 79 char ruler):

Is there anyway to make the lines in the dispersion command come forward in a plot and allow the fill in the dispersion parameter be transparent so all of the lines I am using to note confidence intervals are shown? ------------------------------------------- Joe King, M.A. Ph.D. Student University of Washington - Seattle 206-913-2912 jp@joepking.com

In the "filled bands" part of xYplot of the Hmisc package, is there a way to have multiple bands with multiple lines? or does it just allow one for now? So I had an example bit ago had a made up line and CI, now if I wanted to make a second line with a CI filled in can I put them on the same plot? x<-seq(1,10,1) y<-seq(1,10,1) ci<-y*.10 ciupper<-y+ci

Ok so I am trying to add a subtitle to my xYplot using Hmisc and I have some dummy code of x<-seq(1,10,1) y<-rev(seq(1,10,1)) ci<-y*.10 ciupper<-y+ci cilower<-y-ci this code works fine: xYplot(Cbind(y,ciupper,cilower)~x, type=c("b"),plot.points = TRUE, method='filled bands', main='main title') but when I add sub=. at the end and use this

Here's my command copied from a shell script:\ rsync --verbose --progress --stats --compress --rsh=/usr/bin/ssh --recursive --times --perms --links \ /home/* trt@xxxxxx.xxxxxxx.xxx:/remotebackups/ Here's some (a small part) of the output: jk/.recently-used 253 100% 0.00kB/s 0:00:00 rsync: recv_generator: mkdir "jk/.secpanel/.runfiles": Permission denied (2) stat

My question is about the "Signif. codes" and the p-value, specifically, the output when I run summary(nameofregression.lm) So you get this little key: Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 And on a regression I ran, next to the intercept data, I get '***' Coefficients: > > Estimate Std. Error t value Pr(>|t|) > >

Dears, I'm a college student and In doing my statistics homework. I use R with SEM package as my tool for sem analysis, but my teacher told me AMOS is more suitable for such analysis. Could someone help tell me whether it is true that some commercial software is better accepted in academic fields? Sorry if I should not post such topics here. -- Best Regards, Reeyarn T. Lee Accounting