similar to: Plotting the mean of data

I'm writing an publication in two column format and need to shrink some plots. After increasing the axis labels it does not look nice at all. The y-axis label and tick labels almost touch each other and the x-axis tick labels expand into the plot instead of away from it. Is there a better way than "cex" to control the: 1) font size of axis and tick labels 2) font thickness 3)

Hi all. If I run the simple regression when x is a categorical variable ( x <- factor(x) ): > MyFit <-coxph( Surv(start, stop, event) ~ x ) How can I get the overall p-value on x other than for each dummy variable? > anova(MyFit) does NOT provide that information as previously suggested on the list. All the best, Kare [[alternative HTML version deleted]]

I'd like to avoid looping through an array in order to change values in the array as it takes too long. I red from an earlier post it can be done by "do.call" but never got it to work. The Idea is to change the value of "y" according to values in "x". Wherever "x" holds the value 3, the corresponding value in "y" should be set to 1. So I

Dear R-gurus! Is it possible within boxplot to break the y-scale into two (or anything)? I'd like to have a normal linear y-range from 0-10 and the next tick mark starting at, say 60 and continue to 90. The reason is for better visualising the outliers. All the best, Kare [[alternative HTML version deleted]]

R-gurus... I've got a 5 column dataframe where I'd like to plot each ID's "b" against "c" with "b" in ascending order (within the same ID). How do I sort "b" so that the other variables are altered equally? ID a b c d 101 1 240 26.7 21.85 101 2 335 21.8 21.85 101 3 1387 26.6 21.85 101 4 877 24.1 21.85

Hi r-helpers... Why do I get this strange huge jump of 36524 days when changing "origin" from 1969-01-01 to 1968-12-31. It should still be close to zero! This really messes up my calculations of follow-up times in my analyses. > julian(strptime("010169", format = "%d%m%y"),origin = as.Date("1969-01-01")) > Time difference of -0.04166667 days >

Is there a function providing more descriptive statistics than "summary()"? I'm working with a coxph analyses and would like to have more info on certain numbers. If my call is something like: Call: coxph(formula = Surv(followup, CasesCancer) ~ age + BMI + parity + HRT) I'd like to know: * How many CasesCancer was excluded (not only the total number of excluded due to

Dear R-helpers, I'm for sure not familiar with R, but it seem like a nice sofware tool, so I've decided to try using it. Here is my problem I just can't figure out: I'd like to do least square fit of a straight horizontal (a = 0) line y = ax + b through some data points x = (3,4,5,6,7,8) y = (0.62, 0.99, 0.83, 0.69, 0.76, 0.82) How would i find b????? All the best, Ked

Hello r-help! I have data with two kind of ratings on status of 100 occupations. The first kind of rating is on the percieved "objective" status that these occupations have in society at large, and the second kind or rating is on the status that the respondents think that these occuption *should* have. The ratings were originally integer values in the rage 1-9, but in the current data,

May be you are also not familiar with statistic. the solution of min \sum_{i=1}^{n} (y_{i}-b)^{2} is the mean. So the solution is b<-mean(y) Justin BEM Elève Ingénieur Statisticien Economiste BP 294 Yaoundé. Tél (00237)9597295. ----- Message d'origine ---- De : Kåre Edvardsen <ked@nilu.no> À : R-help <r-help@stat.math.ethz.ch> Envoyé le : Vendredi, 8 Décembre 2006,

It seems that you have load the "survival" package date.mdy is a function from this one. In this function the "origin" of the time is the first day of 1970 in the base package the origin is the first day of 1960 it's very curious... Benjamin Esterni France From: "Vegard Andersen" <vegard.andersen@ism.uit.no> Subject: [R] Date conversion problem using

Hello! I am using the coxph() function for counting process data. I want to include an intervening event as one of my covariates. In order to do this I have split the relevant observations in my data at the time of intervention. But I have not found any way to "inform" coxph() of the id of these observations. The result of this is that coxph() interprets the split data as

Hi Nilu, Nilanjan Bhowmik wrote: > Is postgress passdb backend submitted by Hamish patch available in the > CVS? > If true, then please put a post in the newsgroup and let us know. > > I am ready to test the patch when it is part of the CVS since it is > easier to send you the feedback. Yes, the patch is currently in the SAMBA_3_0 branch of CVS and will also be in the

Hello, We are a group of PhD students working in the field of toxicology. Several of us have small data sets with N=10-15. Our research is mainly about the association between an exposure and an effect, so preferrably we would like to use linear regression models. However, most of the time our data do not fulfill the model assumptions for linear models ( no normality of y-varible achieved even

Hi Gang, I've got the latest SVN branch of 1.4 downloaded onto SUSE 11.0. Everything is happy EXCEPT, I can't get fax to be recognized by make menuselect. I tried copying app_rxfax.c and app_txfax.c to the apps directory and starting again from ./configure, but no joy. Any suggestions? Danny Nicholas -------------- next part -------------- An HTML attachment was

Hi! I'm comparing the differences in contaminant concentration between 2 different groups of people ( N=36, N=37). When using a simple linear regression model I found no differences between groups, but when evaluating the diagnostic plots of the residuals I found my independent variable to have deviations from normality (even after log transformation). Therefore I have used bootstrap on

I'm trying to add 'gplots' from install.packages("gplots", lib = "/usr/lib/R/library", dependencies = TRUE) on a linux host, but R does not seem to figure out there's a new package installed (yes, I've restarted the R-session). I've tried the default, and different library folders, without success. Installation does not report any warnings or bad exit

I'm trying to devide x into tertiles, but ends up with integer limits even x holds one decimal. The analysis is extremely sensitive to the limits and I like to keep them right. How can that be done? quartiles <- quantcut( x[x >= 0], q=seq(0,1, by=(1/3)) > table(quartiles) quartiles [180,344] (344,448] (448,644] 16467 16476 16452 [[alternative HTML version deleted]]

Hello all, I am not a Samba expert by any means, so please bear with me if I make a fool of myself. We run a small network in this office. There is a Windows domain running off of a Debian Linux server, running Linux 2.4.25. There are mostly Windows 2000 and Windows XP machines, but there are still a few users clinging on to Windows 98 (this is because they run specialized testing software

Hi! First of all: I'm a newbie to both statistics and R, so please be patient with me... I do however, like R because I've been programming (pascal, IDL, perl, C etc) and designing models since -92, but never related to statistics. Ok, here we go: I've got a set of 15 people, all of them observed over 10 weeks (10 analysed blood samples) with - let us kall it the A-value - influenced