similar to: Summarising Data for Forrest Plots

Hi everybody, this is a real dummy thing. I sorted a matrix based on a given column, and what I get is right, until it comes to columns of negative and positive values; than, "order" orders everything from max to min in the negative values, and then AGAIN from max to min in the positive values!!! Why isn't everything order from max to min, and that's it? Thank you!!! Attached

Hi, I've lost my mind on it... I have to scatterplot two vectors, grouped by a third variable, with two different dimensions according to whether each cell line in the plot is sensitive or resistant to a given drug, and with a different color for each of 9 tissues of origin. Here's what I've done:

I may be doing this wrong! but I have a function which I have simplified a lot below. I want to pass some 'field names' of a data-frame to the function for it to then do some manipulation of. Here's my code: #build a simple dataset mydataset = data.frame (

I have to study censured datas concernig the occurence of infection at the point of insertion of catheter in patients with renal disease. Catheter may be removed for ather reasons than infection, in this case, the observation is censored. Each has exactly 2 observations. The question are the pronostic factors of infection (the other variables are; age, sex, type of renal disease...). Could you

Hi, I am performing a two-way ANOVA (2 factors with 4 and 5 levels, respectively). If I'm interpreting the output of summary correctly, then the interaction between both factors is significant: ,---- | ## Two-way ANOVA with possible interaction: | > model1 <- aov(log(y) ~ xForce*xVel, data=mydataset) | | > summary(model1) | Df Sum Sq Mean Sq F value Pr(>F) |

Dear members of this list, I'd like to count missing values using the aggregate function. Something like this: count_nas <- function(arg1) { return(sum(is.na(arg1))) } aggregate(cbind(var1, var2, var3) ~ subject + time, data = mydataset, count_nas) It's not working: I end up with a matrix containing zeros, although there are missings in the data frame. I'd highly

Hi list, I am using the capscale function in vegan_2.0-7 to do a constrained principal coordinates analysis, and I kept getting the following error message: Error in Y.r[, oo, drop = FALSE] : subscript out of bounds I googled but I couldn't find an answer. Could anyone tell me why this error msg and what to do? Here is the command I used:

Dear R users, I was wondering how I can replace the values of a vector with the values from in another vector in the same row For example, how can I replace the value of x below with NA when the value of Z in the same row is NA? x <-1:20 z<- c(11, 15, 17, 2, 18, 6, 7, NA, 12, 10,21, 25, 27, 12, 28, 16,17, NA, 12, 10) Many thanks Mintewab ________________________________________ Fr?n:

Hello all, I have a peculiar and particular bug that I stumbled across with ggplot2. I cannot seem to replicate it with anything other than my specific data set. Here is the problem: - when I try to plot a histogram, allowing for ggplot2 to decide the binwidths itself, I get the following error: - stat_bin: binwidth defaulted to range/30. Use 'binwidth = x' to

Hi R experts, I have a data recoding problem I cant get my head around - I am not that great at the subsetting syntax. I have a dataset of longitudinal toxicity data (for multistate modelling) for which I want to also want to do a simple Kaplan-Meier curve of the time to first toxic event. The data for 2 cases presently looks like this (one with an event, the other without), with id representing

Dear friends - We have 25 rats, 14 of these subjected to partial removal of kidney tissue, 11 to sham operation, and then followed for 6 weeks. So far we have data on 26 urine metabolites measured by NMR 7 times during the observation. I have smoothed the measurements by b.splines in fda including a roughness penalty, and inspecting the mean curves for nephrectomized and sham animals indicate

Hey R-users, I think I followed the steps but still couldn't figure this out.. I am creating a personal package and I want to include several datasets in the package. I created a subdirectory 'data' in the package, save a dataset 'test.rda' there, built the package, checked it, installed it. Then I loaded the package and tried load(test), data(test), attach(test), none of them

Hi all - I'm on R 2.5.1 for XP. in the systemfit package, the summary is set to print the McElroy's measure of fit unless it's NULL. When the option saveMemory = TRUE, the McElroy isn't included, instead it defaults to NA. Thus I am unable to use summary.systemfit. > library(systemfit) > example(systemfit) > surfit2 <-

Dear R-helpers, In my dataset I have two continuous variable (A and B) and one factor. I'm investigating the regression between the two variables usign the command lm(A ~ B, ...) but now I want to know the regression coefficient (r2) of A vs. B for every factors. I know that I can obtain this information with excel, but the factor have 68 levels...maybe [r] have a useful command. Thanks,

Dear R users I use Windows XP, R2.5.1 (I have read the posting guide, I have contacted the package maintainer first, it is not homework). In a research project on renal cell carcinoma we want to compute Harrell's c index, with optimism correction, for a multivariate Cox regression and also for some univariate Cox models. For some of these univariate models I have encountered an error

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I am new on R, so I have a maybe naive question: if I have many large data.frames and I use only one or two per session, what's the best way? If all are stored in the actual .Rdata, the system gets slow. On the other hand, I wouldn't like to make a separate package for the data. Should I save it with save() and then remove it with rm() ? Could I reload it then? Thanks for suggestions

Dear all, I'm trying to use the lattice barchart function to obtain a bar plot of a variable for different values of two factors. The thing I'm trying to do is something like this: > barchart(MyVar ~ season | place, data=mydataset) My problem is that the column MyVar has some negative values and I would like them to be represented as bars stacking down from zero instead of what

Dear R-friends, I use optim(par=c(mystartingpoints), fn=myloglikelihoodfunction, gr=NULL, method=c("L-BFGS-B"), ## I would like to do not use any bounds control=list(trace=6, ## just to see what it's going on maxit=c(20000)), ## to be sure the it doesn't stop reaching the max iterations

Hi there, I am having some trouble with the Identify() function, it looks that the identify() function only works on the plot of 2-dimension data set. In high-dimension case , if I use pairs() + identify() in hope to observe all the components of the data point I selected, I get error message. Is there anyway to get around this ? Plus, I also need it to actually compare all the