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Dear list, I tried to use the nparcomp to run some post hoc non-parametric comparison and got and error. Error in uniroot(pfct, interval = interval) : f() values at end points not of opposite sign Appreciate any comments. the command line: >nparcomp(Ulceration~Group,data=test,type='Dunnett',control='Non-treated') Jun =================================================================== data as follows structure(list(Group = c("Duoderm", "Duoderm", "Duoderm", "Duoderm", "Duoderm", "Du...

Dear All, I would like to use R function 'selectFGR' of fine gray model in competing risks model. I used the 'Melanoma' data in 'riskRegression' package. Some of the variables are factor. I get solution for full model but not in variable selection model. Any advice how to use factor variable in 'selectFGR' function. The following R code is produced below

If there are any other users who use AHRQ's SAS code comoanaly2010 and comformat2010 to create comorbidity variables, I thought you might be interested in the following PRELIM code we wrote to mimic its functionality in R. It seems to yield similar results, but may contain errors. Please feel free to comment (kindly) or enhance. I'm sure there are better ways to skin this cat, but we at

On 02/02/2015 03:15 PM, Tim wrote: > What are you exactly searching for? Sounds like he is doing a network install, and is looking for the network path that must be supplied in order to do the install. If he doesn't have a local repository, then he has to supply the first part of the path (e.g. http://..../xyz/ ) and he has to stop at the directory level above .../7/ or some such. I

Dear R users, I try to write an rcode for a paranetric weibull model with unobserved heterogeneity. The data I have are giuven below. ( The data comes from Keiding and Klein artricle published in the Statistics in Medicine 1996) . While the simple weibull model runs perfectly ( I get -2*loglikelihood 1093,905), the weibull frailty model does not run well. The code I write is :

Hi, The following code, from Angelo Canty article on line "Resampling Methods in R: the boot Package, 2002", works fine for Angelo Canty using R 2.6.0 on Windows XP. It also works for me using R 1.2.1 and S-PLUS 2000 on Windows XP after installing the S-PLUS bootstrap library, with slight differences in my outputs. > library(boot) > library(survival) >

Dear Geskus, I want to develop a prediction model. I followed your paper and analysed thro' weighted coxph approach. I can develop nomogram based on the final model also. But I do not know how to do internal validation of the model and subsequently obtain calibration plot. Is it possible to use Wolbers et al Epid 2009 approach 9 (R code for internal validation and calibration) . It is

Hello everyone, I wanted to ask if there is an R-package to fit the following Poisson regression model log(\lambda_{ijk}) = \phi_{i} + \alpha_{j} + \beta_{k} i=1,\cdots,N (subjects) j=0,1 (two levels) k=0,1 (two levels) treating the \phi_{i} as nuinsance parameters. Thank you very much -- -Tony [[alternative HTML version deleted]]

Dear samba-list! I just upgraded our linux-file server from the last samba version (1.19.-something??) to the 2.0beta3 since the speed-up effect seemed worth a try. I did this over the weekend to keep our network functional workdays... But now I've seen that only me can write and read properly from the different shares. The other users (I set up user level security as before) have some

Dear Raja, A Fine and Gray model can be fitted using the standard coxph function with weights that correct for right censoring and left truncation. Hence I guess any function that allows to perform stepwise regression with coxph should work. See e.g. my article in Biometrics https://doi.org/10.1111/j.1541-0420.2010.01420.x, or the vignette "Multi-state models and competing risks" in the

Hi, The following code, from Angelo Canty article on line "Resampling Methods in R: the boot Package, 2002", works fine for Angelo Canty using R 2.6.0 on Windows XP. It also works for me using R 1.2.1 and S-PLUS 2000 on Windows XP after installing the S-PLUS bootstrap library, with slight differences in my outputs. > library(boot) > library(survival) >

Hi, The following code, from Angelo Canty article on line "Resampling Methods in R: the boot Package, 2002", works fine for Angelo Canty using R 2.6.0 on Windows XP. It also works for me using R 1.2.1 and S-PLUS 2000 on Windows XP after installing the S-PLUS bootstrap library, with slight differences in my outputs. > library(boot) > library(survival)

Hi, The following code, from Angelo Canty article on line "Resampling Methods in R: the boot Package, 2002", works fine for Angelo Canty using R 2.6.0 on Windows XP. It also works for me using R 1.2.1 and S-PLUS 2000 on Windows XP after installing the S-PLUS bootstrap library, with slight differences in my outputs. > library(boot) >

FYI to all: I've updated the design document to include the newly disclosed variants 1.1 and 1.2 (collectively called Bounds Check Bypass Store or BCBS). There is no change to the proposed implementation which can already robustly mitigate these variants. I've also updated my patch as we have very significant interest in getting at least an early "beta" version of this into the