similar to: CKD-Epi formula

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)"

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

All, I've been using "sub" (subtitle) instead of "main" such that captions are below figures produced by xyplot. This works fine and captions are on a single line. However, when I try this for bar plots with error bars (altering the error.bars function form Crawley's The R Book, see below), the captions are split on more than 1 line. Is there a way to get the

Hi, I am trying to do simple linear regression using dates in R but receiving error messages. With the data shown below, I would like to regress x on y. x y 11/12/1999 56.8 11/29/1999 17.9 01/04/2000 27.4 1/14/2000 96.8 1/31/2000 49.5 R gives the following error messages after reading the linear regression command: Error in storage.mode(y) <-

Dear friends. I wanted to reproduce a sheet of paper useful for plotting the reciprocal of some biochemical variable (creatinine) over time (Bleyer Am J Kidney Dis 34:576-578,1999). Time on X axis with units years and months. On Y axis, 1/creatinine, but with the original creatinine value indicated - to make it easier for people to use it. When using the graph, the linear decrease in 1/crea over

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

Dear Rui, >From my understanding of time-dependent covariates (not an expert but have been working on a similar problem), it would appear that the coding of the status column is not correct. Unless you have observed an event at each interval you should only have status=1 for the last interval. In your example I see 3 in total. Also, I think that if "end" is proportional to your

Dear all, Currently, I am doing a research project about serum sodium levels and falling. I am doing my analysis in R. I am performing the multiple imputation right now. I want to perform a survival analysis later, but therefore I need to specify the Nelson-Aalen estimator. My dataset is called DF1, the event indicator is Falls and the time variable is Time. The code that I use is as follows:

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:

Hard to tell from the info you are giving us. I assume this regards the "mice" package? One way to proceed is to set options(error=recover) which will dump you into the browser() environment when the error occurs and you can oka around and see what the value of variables was at the point of the error. This could give you a clue about what is going on. -pd > On 22 May 2018, at 15:29

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 very general question and I think for you maybe very easy, but I am not able to solve it. I have a dataset and that dataset contains the variable Anxiolytics. This variable is coded as 0, 1, 2. The variable looks as follows: > summary(DF$Anxiolytics) 0 1 2 NA's 1102 0 20 440 You can see that the variable is coded as 0, 1, 2, but group 1

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

With indexed dir enabled, now we use ocfs2_dir_lookup_result to wrap all the bh used for dir. So remove the 2 unused variables. Signed-off-by: Tao Ma <tao.ma at oracle.com> --- fs/ocfs2/namei.c | 4 ---- 1 files changed, 0 insertions(+), 4 deletions(-) diff --git a/fs/ocfs2/namei.c b/fs/ocfs2/namei.c index 2220f93..33464c6 100644 --- a/fs/ocfs2/namei.c +++ b/fs/ocfs2/namei.c @@

I was trying to optimize a minimum memory VM and realized that this process was taking up over 560M of virt memory. On googling, it seems to be a known issue and doesn't seem to be needed except for graphical desktop. Although virt memory isn't actual memory usage, the daemon is still taking up almost 4MB of limited memory, which on a VM with only 384MB feels relatively significant to me.

Hi again, Anyone has an idea how to debug this problem? I tried nearly everything possible, including disabling devices in the BIOS and in CLI mode. I even replaced the CD-ROM drive with another one, just in case it is faulty. The problem persists... The thing that is hanging the probing session comes after PLIP. That's where the boot process always stops... Next thing is to remove the hard

Hi, I have been examining large data and need to do simple linear regression with the data which is grouped based on the values of a particular attribute. For instance, consider three columns : ID, x, y, and I need to regress x on y for each distinct value of ID. Specifically, for the set of data corresponding to each of the 4 values of ID (76,111,121,168) in the below data, I should invoke

Hi all, I am trying to detect association between a covariate and a disease outcome using R. This covariate shows time-varying effect, I add a time-covariate interaction item to build Cox model as follows: COX <- coxph(as.formula("Surv(TIME,outcome)~eGFR_BASE+eGFR_BASE:TIME"),ori.data); coef exp(coef) e(coef) z p eGFR_BASE

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Hi, I'd like to put a 60GB hard disk into Gateway 2000 Pentium 150 (from '96 or '97 or so I think) running FreeBSD 4.8 RELEASE. Can anybody tell me how successful this is likely to be? Will I be able to use the full capacity of the drive? I seem to recall that the trick with large hard disks and old BIOSes is to disable the drive in

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"