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Thank you to Peter Dalgaard, who provided help for some of this solution. It is still not ideal since the dots which are equidistant in the x-direction ideally should respect the reciprocal scale in the y-direction. op <- par("cex"= 0.7) x<-y<-NA plot(x,y,xlim=c(0,10),ylim=1/c(2000,70), axes=F) box() axis(1)

Dear Colleagues   I have the following code that generates a boxplot for one specific labtest:   boxplot.n(LBSTRESN~COHORT, main="Boxplot of laboratory data for XLXXX-XXX test=Creatinine", subset = LBTEST=="Creatinine", xlab = "Cohort Number", ylab = "Units = umol/L", varwidth=TRUE   I would like to know if there is a way to loop through the dataset and

I am running the sm.density.compare function amd I am getting the following error:   my code is  > sm.density.compare(LBSTRESN,COHORT,xlab="Units = umol/L"subset = LBTEST=="Creatinine")   Error in if (from == to) rep.int(from, length.out) else as.vector(c(from,  :   missing value where TRUE/FALSE needed   I do not understand the error and I have had no help when searching

Often, when exploring a dataset, I'd like to plot several very different Y variables against the same X variable, in panels stacked one over the other. Is there an easy way to do this? I'd like to achieve an elegant look similar to the look achieved by lattice in conditioned plots--for instance no space between panels. But unlike in straightforward conditioned plot, each panel may be on a

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

Hi all, I have a question about multiple imputation within the MICE package. I want to use passive imputation for my variable called X, because it is calculated out of multiple variables, namely Y, Z. Let's give an example with BMI. I know, that if I want to use passive imputation for BMI, I can use the following command: meth["BMI"] <- "~I(weight/(height/100)^2)"

Dear friends. I have a paper (details below) examining the risk of renal failure after an operation. A logistic regression was done, and the coefficients to two regressors (age and creatinine) plus intercept with standard errors are given. These coefficients must be dependent in estimation, and when no details are given, I thought how I could most informatively get an impression as to how

Hi all, I have a question and I do not know If I am at the right place to ask this question. But is there someone that has the formula of CKD-Epi in code in R? I have tried a lot of loops, but none of the approaches give me the right answer. Is there someone who has this formula coded? Thank you! [[alternative HTML version deleted]]

I making an xyplot and the y label is too long and needs to be in two rows, but when I brake it there is a huge gap between the last text string and the expression, and I can't get rid of it. Any ideas? Data: structure(list(Temp = c(8L, 8L, 8L, 8L, 8L, 8L, 12L, 12L, 12L, 12L, 12L, 12L), CO2 = c(380L, 380L, 380L, 750L, 750L, 750L, 380L, 380L, 380L, 750L, 750L, 750L), Treat = structure(c(3L,

Hi! Here is some output from an str command: > str(CO2) Classes ‘nfnGroupedData’, ‘nfGroupedData’, ‘groupedData’ and 'data.frame': 84 obs. of 5 variables: $ Plant : Ord.factor w/ 12 levels "Qn1"<"Qn2"<"Qn3"<..: 1 1 1 1 1 1 1 2 2 2 ... $ Type : Factor w/ 2 levels "Quebec","Mississippi": 1 1 1 1 1 1 1 1 1 1 ... $

I making an xyplot and the y label is too long and needs to be in two rows, but when I brake it there is a huge gap between the last text string and the expression, and I can't get rid of it. Any ideas? Data: structure(list(Temp = c(8L, 8L, 8L, 8L, 8L, 8L, 12L, 12L, 12L, 12L, 12L, 12L), CO2 = c(380L, 380L, 380L, 750L, 750L, 750L, 380L, 380L, 380L, 750L, 750L, 750L), Treat = structure(c(3L,

Hello , I'm new to R and don't really understand how to use the function "apply" instead of a "for loop", particularly for a function with multiple entries. I have a big data file and would like to apply a function in multi thread to accelerate the processus. I have a data frame containing values of* CO2 in ppm (resp[i,6])* that I want to convert in umol of CO2

Larry, You found a data set that kills coxph. I'll have to think about what to do since on the one hand it's your own fault for trying to fit a very bad model, and on the other I'd like the routine to give a nice error message before it dies. In the data set you sent me the predictor variable is very skewed: > quantile(anomaly1$CREAT, c(0, .5, .9, .999, 1)) 0% 50%

Dear friends. I have trobpe with path. Below I have tried to paste a path and file name but it will not work > path <- "D:/rw0641/own/own/procedures/GFR_TIME" > path [1] "D:/rw0641/own/own/procedures/GFR_TIME" > path1 <- paste(path,"gfr.txt",sep="/") > path1 [1] "D:/rw0641/own/own/procedures/GFR_TIME/gfr.txt" -- this is good

Hi All, I'm trying to run nls on the data from the study by Marske (Biochemical Oxygen Demand Interpretation Using Sum of Squares Surface. M.S. thesis, University of Wisconsin, Madison, 1967) and was reported in Bates and Watts (1988). Data is as follows, (stored as mydata) time bod 1 1 0.47 2 2 0.74 3 3 1.17 4 4 1.42 5 5 1.60 6 7 1.84 7 9 2.19 8 11 2.17 I then

Dear R community, I am trying to fit an nlme model where I want to estimate the fixed effects of two treatments on the parameters on the following equation Photo~(a*(1-exp(-c*PARi/a)))-b I was able to fit a simple model without covariates following the method described in Mixed-Effects Methods and Classes for S and S-PLUS, version 3.0, but when I add the covariates, I get the error "

Dear Ladies and Gentlemen, I have a fairly large database (N=13,000) and a single main categorical discriminator between the groups. I want to look at the time course of a number of continuous biochemical variables over chronologic age. Therefore I believe I need to prepare hexbinplots in two columns with simple regression lines in them (with useOuterStrips (in library(latticeExtra) if

Hi. I'm going to introduce the R-package for a group of medical doctors later this week and is a little confused about there use of a test named "willcoxon-pratt" for testing if the clinical and biochemical markers has decreased significantly after the use of some drugs for a group of patients. Looking into the R-functions I would in R recommand using a matched-pairs Wilcoxon

Mª Luz, si el comando de Carlos te devuelve 0 es que no hay NA's. Da igual que tus columnas sean caracteres o número. Lo que intuyo es que tienes celdas con la frase "NA" que interpretas como NA. Mandanos el summary de tu data.table y lo vemos... ----- Mensaje original ----- De: "MªLuz Morales" <mlzmrls en gmail.com> Para: "Carlos J. Gil Bellosta"

Hi all, How does one create a matrix of values in a loop. For example, I have 46*70 matrix with columns giving the values for some blood tests performed upon the 46 patients(rows). I want to perform a simple test of normality (shapiro-wilk test) upon each of the biochemical tests for the 46 patients. Can somebody suggest the syntax for such a loop. For the data x, I wrote the following loop which