similar to: cox goodness of fit

I would like to join repeated measures for patients across two visits using a line. The program below uses symbols to represent each patient. Basically, I would like to join each pair of symbols. library(lattice) patient <- c(1,2,3,4,5,6,7,8,9,1,2,3,4,5,6,7,8,9) var <- c(826,119,168,90,572,323,122,10,42,900,250,180,120,650,400,130,12,33) visit <- c(1,1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2,2)

I would like to set the y axis limit of an xyplot using the object 'ylimit', but receive this error: [1] 990 Error in extend.limits(limitlist[[i]], axs = axs) : improper length of lim I get the same error if I use ylim. library(lattice) trellis.device(col = FALSE, theme = lattice.getOption("col.whitebg")) name <- "Variable name" symbols <-

I have an outlier that I would still like to display, but would prefer to shorten the axis. For example, display 0% - 40%, and 90% - 100%. Is this possible? I am using an xyplot. Thanks Murray -- Murray Pung Statistician, Datapharm Australia Pty Ltd 0404 273 283 [[alternative HTML version deleted]]

Is there any way of adding text to a density plot? I have had a go using the text() function but I think the error is because this function doesn't work with densityplot(). Alternatively, I understand I can achieve pretty much the same result if I plot a density kernel estimate using plot() (which allows text()), but I do prefer densityplot(). Also, is it possible to specify the dimensions

I have checked out the help files, but cannot find details on how to use maths characters in ylab. Instead of m^2, I would like the 2 in superscript, if possible. I would also like to place more padding on the label so that the label is not obscured by the horizontal numbers. y <- 1:10 x <- rnorm(10,50000,2000) plot(x ~ y, ylab = 'Y Label (m^2)', las = 1, type =

I need an object created in a user defined function to be accessible to another user defined function. I am fairly certain the object is correctly created as it prints when I use the return() function, however the 2nd function seems unable to use it. I am guessing objects created in functions are not globally accessible, is this correct? What is an appropriate way to pass the object to the

Is it possible to add standard error bars to the means on interaction plots? Thanks Murray -- Murray Pung Statistician, Datapharm Australia Pty Ltd 0404 273 283 [[alternative HTML version deleted]]

To differentiate between groups on the barplot, I guessed that col = colr[test$group] would have worked. How can I do this? Many Thanks Murray test <- structure(list(patient = 1:20, score = c(100, 95, 80, 75, 64, 43, 42, 40, 37, 35, 30, 29, 27, 26, 23, 22, 19, 18, 17, 16), group = c(1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 1, 0)), .Names = c("patient",

How can I get the Log - Rank p value to be output? The chi square value can be output, so I was thinking if I can also have the degrees of freedom output I could generate the p value, but can't see how to find df either. > (survtest <- survdiff(Surv(time, cens) ~ group, data = surv,rho=0)) Call: survdiff(formula = Surv(time, cens) ~ group, data = surv, rho = 0) N Observed

Are there ways to load a csv file without row.names by read.csv? Thanks. [[alternative HTML version deleted]]

Is it possible to format the x axis, so that days are spaced proportionately? i.e. a larger space between 50 & 100, than 0 and 5? Have not had any luck with axis.POSIXct(). Many thanks Murray try <- structure(list(visit = structure(as.integer(c(1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5)), .Label = c("Screening", "0",

Hi list, I was trying to use "predict.coxph" to calculate martingale residuals on a test data, however, as pointed out before http://tolstoy.newcastle.edu.au/R/e4/help/08/06/13508.html predict(mycox1, newdata, type="expected") is not implemented yet. Dieter suggested to use 'cph' and 'predict.Design', but from my reading so far, I'm not sure they can

I am looking for a good probability book that describes convergence in distribution. I have looked through Introduction to Probability by Charles M. Grinstead, J. Laurie Snell, but I don't find any formal description on convergence in distribution. Could somebody recommend a good book that cover this topic? Thank you!

Full_Name: Rob Strawderman Version: 1.9.1 OS: red hat linux 8 Submission from: (NULL) (128.253.217.211) The following demonstrates the basic problem: [martingale <99>]% rm .RData rm: remove regular file `.RData'? y [martingale <100>]% R R : Copyright 2004, The R Foundation for Statistical Computing Version 1.9.1 (2004-06-21), ISBN 3-900051-00-3 [deleted] >

Dear R wizards, I am seeking advice on graphics in R. Specifically, how to manipulate the size and save a plot I have produced using the LDheatmap library. I confess I am relatively new to graphics in R, but I would greatly appreciate any suggestions you may have. LDheatmap produces a coloured triangular matrix of pairwise associations between 600 genetic markers in my dataset.

I am using plot(survfit(Surv(time,status) ~...) and would like to add error bars rather than the confidence intervals. Am I able to do this at specified times? e.g. when time = 20 & 40. leukemia.surv <- survfit(Surv(time, status) ~ x, data = aml) plot(leukemia.surv, lty = 2:3,xlim = c(0,50)) #can i add error bars at times 20 & 40? legend(100, .9, c("Maintenance", "No

Hi, is there any method for goodness of fit testing of an (as general as possible) univariate distribution with parameters estimated, for normal, exponential, gamma distributions, say (e.g. the corrected p-values for the Kolmogorov-Smirnov or Chi-squared with corresponding ML estimation method)? It seems that neither ks.test nor chisq.test handle estimated parameters. I am aware of function

Hi Gurus: In the coxph() objects in Survival package, there is an attribute called residuals. Usually, there are several kinds for censored survival data. I can't seem to find in the documentation as to which one this is calculating. Anyone knows? Karen _________________________________________________________________ [[alternative HTML version deleted]]

Dear all, I am looking for a good reference on "Survival analysis". I am looking for a booking containing both applications and Maths. Explaining different methods in survival analysis .... Many thanks Bernard --------------------------------- [[alternative HTML version deleted]]

Hi, Recommending to go Digium because of an OpenBSD issue with the Sangoma A104D is quite funny to say the least since neither is the TE407P supported in BSD by Digium. So the recommendation is useless to the person who originally requested for a comparison between the two products. If someone wanted to send back the A104D, he could have taken advantage of Sangoma's 30 day money back