similar to: xyplot plot with groups

Dear all, my aim is to estimate the efficacy over time of a treatment for headache prevention. Data consist of long sequences of repeated binary outcomes (1 if the subject has at least 1 episode of headache , 0 otherwise) on subjects randomized to placebo or treatment. I have fit a logistic regression model with Huber-White cluster sandwich covariance estimator. I have put in the model the

Dear R-help - Thanks to those who replied yesterday (Christos H. and Thomas L.) regarding my question on coxph and model formula, the answers worked perfectly. My new question involves the following. I want to run several coxph models (package survival) with the same dataset, but different subsets of that dataset. I have found a way to do this, described below in functions subwrap1 and

Dear R users, I am trying to use xyplot to draw group mean and CI. The following is the sample code. But I want: 1. Use different colors and symbols to draw individual points, CI and the lines connect group means from different time points; 2. Add jitters to x axis to allow CIs not be overlapped Could anyone modify the attached code to achieve this? Thanks library(lattice)

Hi all, I asked this before the holiday, didn't get any response. So would like to resend the message, hope to get any fresh attention. Since this is not purely lme technical question, so I also cc-ed R general mailing list, hope to get some suggestions from there as well. I asked some questions on how to analyze longitudinal study with only 2 time points (baseline and a follow-up)

Hello, I am new to R and have tried to search similar questions but could not find exactly what I am looking for, but I apologize if the question was already asked. I have 10 different treatments and want to know whether they affect the sex ratios of insect emergence. After running the glms I got this table: Df Deviance Resid. Df Resid. Dev F Pr(>F) NULL

Hi - I am not R expert and I would appreciate your time if you can help me about my xyplot question. I would like to add text (p-value) in a 4 panels xyplot. I thought panel = function{} should work but I am not sure where I did it wrong. The error message from the following code is "Argument subscripts is missing with no default values" xyplot(GLG ~ PD | factor(TRT) , groups =

Hi all, I am running the following model: > glm89.nb <- glm.nb(AvGUD ~ Year*Trt*Micro) where Year has 3 levels, Trt has 2 levels and Micro has 3 levels. However when I run it has a zero inflated negative binomial (as I have lots of zeros) I get the below error message: > Zinb <- zeroinfl(AvGUD ~ Year*Trt*Micro |1, data = AvGUD89, dist = "negbin") Error in optim(fn =

#Dear All, #I'm having a bit of a trouble here, please help me... #I have this data set.seed(4) mydata <- data.frame(var = rnorm(100), temp = rnorm(100), subj = as.factor(rep(c(1:10),5)), trt = rep(c("A","B"), 50)) #and this model that fits them lm <- lm(var ~ temp * subj, data = mydata) #i want to

I tried to post this a few times last week and it seems to have got stuck somehow so I'm trying from a different email in the hope that works. If somehow this has appeared on the list 20 tiems and I never saw any of them I apologize ;-) I'm basically an R-newbie. But I am VERY computer literate. But this has me stumped... All the examples for using the rmeta package to create a

Consider the following plot that shows separate regression lines ~ age for each subject in the Pothoff-Roy Orthodont data, with separate panels by Sex: library(nlme) #plot(Orthodont) xyplot(distance ~ age|Sex, data=Orthodont, type='r', groups=Subject, col=gray(.50), main="Individual linear regressions ~ age") I'd like to also show in each panel the pooled OLS

Hi! I have a dataframe like this: dat=data.frame(Age=c(rep(30,8),rep(40,8),rep(50,8)),Period=rep(seq(2005,2008,1),3),Rate=c(seq(1,8,1),seq(9,16,1),seq(17,24,1)),Sex=rep(c(rep(0,4),rep(1,4)),3))attach(dat)dat    Age Period Rate Sex1   30   2005    1   02   30   2006    2   03   30   2007    3   04   30   2008    4   05   30   2005    5   16   30   2006    6   17   30   2007    7   18   30   2008  

R-helpers: I have a dataset that has 168 subjects and 12 variables. Some of the variables have missing data and I want to use the multiple imputation capabilities of the "mice" package to address the missing data. Given that mice only supports linear models and generalized linear models (via the lm.mids and glm.mids functions) and that I need to fit Cox models, I followed the previous

Hello, I have written code to plot an xyplot as follows: library(lattice) xyplot(len~ageJan1|as.factor(cohort),groups=sex,as.table=T,strip=strip.c ustom(bg='white',fg='white'),data=dat, xlab="Age (January 1st)",ylab="Length (cm)",main="Linear models for male and female cod, by cohort",type='p',

Hello, I have a problem with my script. I don'y know how to apply subtitles. I have 9 charts per page (for combination of 3 blocks and 3 treatments). I want to have subtitles for this interaction (e.g. Block A Trt 1, Block A Trt 2, ...) MBE$bt<- interaction(MBE$Block,MBE$trt) par(mfrow=c(3,3)) for(i in unique(MBE$bt)){ ss <- MBE$bt==i plot(MBE$Year[ss], MBE$DBH[ss])

Hello, I have been trying to make a graph that have error bars and text at specific position. I used the following code from the help file of xYplot(Hmisc) as an example except I add a myPanel function, which is just supposed to add letters from the alphabet at the position aligned at y = 3. It constantly gives me error: "Error using packet 1 argument "subscripts" is

I have two questions related to plotting predicted values for a linear mixed model using xyplot: 1: With a groups= argument, I can't seem to get the key to appear inside the xyplot. (I have the Lattice book, but don't find an example that actually does this.) 2: With lme(), how can I generate confidence bands or prediction intervals around the fitted values? Once I get them, I'd

I would like to create a plot of y vs x with different treatments where the points are actually the letter of the treatment. Here is the code: A<-as.matrix(rnorm(10,10)) B<-as.matrix(rnorm(10,9.5)) C<-as.matrix(rnorm(10,10.5)) Y<-as.matrix(rnorm(30,13)) X<-rbind(A,B,C) nA<-matrix("A",10,1) nB<-matrix("B",10,1) nC<-matrix("C",10,1)

In the hypothetical example below, how do I add two segments() into the two panels, respectively? Say segments(x0=5, y0=10, x1=5, y1=20) on the left and segments(x0=15, y0=-10, x1=15, y1=-2) on the right? Many thanks in advance, Yuelin Li. ps. part of the code came from a solution given by Deepayan Sarkar. ------------------- library(lattice) set.seed(12345) x <- 0:20 y.male.obs <- - 1.2

I've been experimenting with drop1 for my biostatistics class, to obtain the so-called Type III sums of squares. I am fully aware of the deficiencies of this method, however I feel that the students should be familiar with it. What I find baffling is that when applied to a fully balanced design, you obtain different sums of squares. I've used this for several years in Splus and R and never

My apologies to the list for sending this without adequate research. I have found my answer; please ignore! Thanks. I've been experimenting with drop1 for my biostatistics class, to obtain the so-called Type III sums of squares. I am fully aware of the deficiencies of this method, however I feel that the students should be familiar with it. What I find baffling is that when applied to a fully