similar to: graphics - joining repeated measures with a line

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 <-

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

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]]

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 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

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.

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",

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]]

Is there an implementation of the Cox-Snell residuals / Nelson-Aalen plot for goodness of fit? Or otherwise is there an appropriate Goodness of Fit diagnostic? Thanks Murray -- Murray Pung Statistician, Datapharm Australia Pty Ltd 0404 273 283 [[alternative HTML version deleted]]

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

Dear List I am new to R and to the list and will try best as I can be clear and concise. My apologies if anything I write contravenes the posting code on this list. I would also like to say I have run through most of the material on the R website before writing this email however, I am stuck. Here is what I want to do and what I have done 1. Read a comma seperated text file into R I have used

I'd like to paste a superstring with a number in an object. Thanks for any help. Murray mycor <- cor(1:10,1:10) plot(1:10,1:10) text(8,2,paste(expression(R^2)," = ",mycor)) [[alternative HTML version deleted]]

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

dear List I have a dataset with blood measurements at 5 points in TIME (0,30,60,90,120) taken on 3 VISITS (same subjects). the interest is to compare these measurements between Visits, overall and at the different time points. I have problems setting up repeated measures ANOVA with 2 repeated measures (VISIT and TIME) (and then doing post hoc testing) or doing it with a linear mixed model ( both

Dear R-helpers, This may sound simple to you, but I'm a beginner in this, so please be forgiving. I have a following problem: two analytes were measured in patient's blood on 4 occasions: ProteinA and ProteinB. How to correctly evaluate correlation between ProteinA and ProteinB? I tried: x <- data.frame(Patient.ID=rep(1:10, each=4), Visit=rep(c(1:4),10), ProteinA=rnorm(m=10,

Dear R help gurus, I have the following problem and I would be delighted if you could help me. >From a large (1500) cohort of patients we have been taking some measurements (ECG measurements, but its not important). The measurements are ordinal in 4 grades (Grade I-IV, grade IV being the most severe form). Every patients has been measured several times (usually once per year). The

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",

I have a dataset that I'm trying to rearrange for a repeated measures analysis: It looks like: patient basefev1 fev11h fev12h fev13h fev14h fev15h fev16h fev17h fev18h drug 201 2.46 2.68 2.76 2.50 2.30 2.14 2.40 2.33 2.20 a 202 3.50 3.95 3.65 2.93 2.53 3.04 3.37 3.14 2.62 a 203 1.96 2.28 2.34 2.29 2.43 2.06 2.18 2.28 2.29 a

All, I have a repeated measures data frame and was wondering if the covariance matrix can be calculated via some created indexing or built-in R function. Specifically, say there are 3 variables, where potassium concentration is measured 6 times on each patient. Patient number (discrete) Time (1 to 6, discrete) Potassium (continuous variable) I want the covariance/correlation matrix for the