similar to: Adjusting confidence intervals for paired t-tests of multiple endpoints

Hi all, I want to plot the grouped means of some variables. The dependent variables and the grouping factor are stored in different columns. I want to draw a simple line-plot of means, in which the x-axis represents the variables and y-axis represents the means. The means of the groups should be connected by lines. So far, the only function that I could find comes closest to what I'm

In http://tolstoy.newcastle.edu.au/R/e2/help/06/10/3064.html a method was given for converting a frequency table to an expanded data frame representing each observation as a set of factors. A slightly modified version was later included in the NCStats package, only on http://rforge.net/ (and it has too many dependencies to be useful). I've tried to make it more general, allowing an input

Hi I have a dataframe in which some subjects appear in more than one row. I want to extract the subject-rows which have the minimum date per subject. I tried the following aggregate function. attach(dataframe.xy) aggregate(Date,list(SubjectID),min) Unfortunately, the format of the Date-column changes to numeric, when I'm applying this function. How can I preserve the date format? Thanks

Hi, I have the following problem with ggplot2: When I specify black contours for bars in a barplot, ggplot automatically shows diagonal lines in the legend boxes. Is there a way, to remove these diagonal lines? Here's a simple example: library(ggplot2) df<-data.frame(x=gl(6,1),y=rnorm(6,100,50)) ggplot(df,aes(y=y,x=x,fill=x))+geom_bar(aes(group=x),colour='black',size=1)+

Sorry, for asking the same question again, but I got no reactions the last time. Maybe it was just overseen by the experts. I'm using the xtable function with Sweave and Lyx and I would like to know how to get automatic line breaks for long strings in a column of the table. I've learned from the Lyx wiki that the Latex command \linebreak produces table cells with multiple lines. I tried to

Hello I would like to pass a model formula as an argument to the with.mids function from the mice package. The with.mids functon fits models to multiply imputed data sets. Here's a simple example library(mice) #Create multiple imputations on the nhanes data contained in the mice package. imp <- mice(nahnes) #Fitting a linear model with each imputed data set the regular way works

Dear All, I met problems when doing contrast and now really need some help in the model below: Fit=gam(y~treat+SEQUENCE+PERIOD+SEX+s(x),data=dat, random=list(SUBJID=~1),correlation=corAR1(form=~1|SUBJID)) And error message keeps coming out when I want to compare the differences between treatments: Diff=contrast(Fit, list(treat=treatment[-placebo.pos]),list(treat="Placebo"),

Dear all, The incredibly useful Hmisc package provides a method to generate summary tables that can be typeset in latex. The Alzola and Harrell book "An introduction to S and the Hmisc and Design libraries" provides an example that generates mean and quartiles for continuous variables, and numbers and percentages for count variables: summary() with method = 'reverse'. I

Hallo! I have two groups (placebo/verum), every subject is measured at 5 times, the first time t0 is the baseline measurement, t1 to t4 are the measurements after applying the medication (placebo or verum). The question is, if there is a significant difference in the two groups and how large the differnce is (95% confidence intervals). Let me give sample data # Data

I am having two problems creating data frames that I have solutions, but they really seem like kludges and I assume I just don't understand the proper R way of doing things. The first situation is I have an set of uneven data vectors. When I try to use them to create a data frame I would like the bottoms of them padded with NAs, without explicitly specifying that. When I do: anxiety.data =

Hi, I am experimenting with using glht() from multcomp package together with coxph(), and glad to find that glht() can work on coph object, for example: > (fit<-coxph(Surv(stop, status>0)~treatment,bladder1)) coxph(formula = Surv(stop, status > 0) ~ treatment, data = bladder1) coef exp(coef) se(coef) z p treatmentpyridoxine -0.063 0.939 0.161

I read in a thread in r-help today that the windows device in 2.6 supports transparency, so I tried an example and had some issues. The density plots should be filled with transparent color in the following example (similar to the points), however the color is "fully" transparent. This works in the Cairo device, but not in the windows device. Thanks, --Matt Matt Austin

All, I can't seem to get auto.key to work properly in an xyplot that is employing panel.text. Specifically, I often change the default grouping colors then use auto.key accordingly, but for some reason the same functionality isn't working for this different type of plot. Any help much appreciated. Cheers, David library("lattice") dat = data.frame( Y = c(rnorm(18,1),

Hello, I have a problem with creating an identity matrix for glmnet by using the contrasts function. I have a factor with 4 levels. When I create dummy variables I think there should be n-1 variables (in this case 3) - so that the contrasts would be against the baseline level. This is also what is written in the help file for 'contrasts'. The problem is that the function

I have problem getting the concept of a nested fixed variable into the nlme scheme. I fear the question is very stupid. In the past I had asked this before, and never got a reply (in other cases, the response was within hours). I also checked the S-list, where several similar enquiries of other people are orphaned. We have a cross-over design, where patient are treated two weeks with placebo,

Dear all, I am trying to create a list, where each list element is a vector of different length arrays that contain 2by2 matrices. To be more specific there are 11 treatments that are compared with placebo (we have 11 comparisons) and each comparison is studied by a different number of trials and each trial has a different number of missing participants in both arms. The length of the list is

How i can perform a Pearson's Chi-squared Test in this data set: | Outcome -----------------+-----------+----------------------------------+ Treatment | Sex | None |Some | Marked | Total -----------------+------------+--------+--------+-------------+ Active | Female | 6 | 5 | 16 | 27

Hi all, I am trying to parse a vector for caliculating minimum in that vector the vector having values like 1 Kontrolle 2 Placebo 3 125mg/kg 4 250mg/kg 5 500mg/kg 6 1000mg/kg hear i tries for comverting it into numeric with using "as.numaric()" function but i got values like 5 6 2 3 4 1 it gives 1000mg/kg is the least one but i have

All, The code below is for a pseudo dataset of repeated measures on patients where there is also a treatment factor called "drug". Time is treated as categorical. What code is necessary to test for a treatment effect at a single time point, e.g., time = 3? Does the answer matter if the design is a crossover design, i.e, each patient received drug and placebo? Finally, what would

Hello, I am using Hmisc summary.formula, latex and Sweave to produce tables for publication. Is it possible to change the formats for binary and continuous variables? I would prefer to show 35 (10%) and 1.5 (1.2-1.8) rather than 10% (35) and 1.2 / 1.5 / 1.8. Here is a simple example: sex <- factor(sample(c("m","f"), 500, rep=TRUE)) age <- rnorm(500, 50, 5) treatment