similar to: Analyzing binary data on an absolute scale and determining conditions when risks become equal between groups

Is there a predict method/syntax which I could use to generate predictions (and other output from predict() methods) if I have the model parameter estimates from a training dataset but not the data used to generate the original model (the models were generated by a collaborator using STATA and for IRB reasons I am not allowed independent access to the original data)? I have the new/testing data

I am interested in a model diagnostic for logistic regression which is normally distributed (much like the residuals in linear regression with are ~ N(0,variance unknown). My understanding is that most (all?) of the residuals returned by residuals.lrm {design} either don't have a well defined distribution or are distributed as Chi-Square. Have I overlooked a residual measure or would it be

Dear All, though my query is not directly with rsync but i thought some of the people must be using rsync & ssh, so i am posting my query here, in case if there is some other group or forum pls let me know so that i won't bother people here(my apologies) actually, i am facing a very strange issue as : my objective is to use rsync from windows m/c with ssh(auto), so i did as ... 1) I

dear sir/madam hello i am trying to run a samba server with linux 7.3 and win xp but loaded rpm of samba of linux 7.2 the thing is that i am able to see the workgroup in windows xp but the contents of it are invisible what could be the prob. the log file is showing following errors 1) smbd/connection.c:yield_connection(62) yield_connection:tdb_delete failed with error record does not exist

Dear All, just to let people configure an email system, I have written an article on it and want that you should go through it, analyse and test it and help me to improve it further, while in case there is any error/mistake or correction is required please let me know. though I am not an expert but your valuable input will help me to understand the mailing system. SendMail + LDAP HowTo.

Dear User, In my previous article published in darpan 28/04/06 I mentioned ? technology is changing rapidly and there could be some unanticipated issues?, so here is the time to look into one... "Date" is one of the well known representation of "Time" and plays a critical role in our life. Just for an example our financial transactions, Important events, various schedules

I have a Windows NT4 domain that I'm considering migrating to Samba. It has three domain controllers, all of which are WINS servers, about 350 computers and around 250 users. It also has a trust relationship with an Active Directory domain. I'd be migrating to three Samba servers backed by LDAP and only one of them running WINS. I'm using the net rpc vampire method described in the

Dear R group: I am compiling a list of available algorithms/macros/software for performing the following types of competing risks analyses: (1) cumulative (crude) incidence regression (2) Gray's K-sample log-rank test for cmulative incidence (3) multi-state models (4) dependent competing risks modeling with (a) copulas, (b) Robin's Inverse probability of censoring weighted (IPCW)

Dear R users: Analysis of the impact of a time-dependent covariate (GVHD or use of steroid after bone marrow transplantation) on two competing endpoints (invasive fungal infection and death) is frequently encountered in the setting of BMT data. Coxph package can be used as the following: for the analysis of GVHD: > gvhd -> coxph(Surv(start,stop,status = =1) ~ GVHD, data=bmt.data)

Dear All, I have analysed time to event data for continuous variables by considering the multivariable fractional polynomial (MFP) model and comparing this to the untransformed and log transformed model to determine which transformation, if any, is best. This was possible as the Cox model was the underlying model. However, I am now at the situation where the assumption that the competing risks

Hello! Is there any possibility in R to carry out competing risks analysis with left- truncated data (late entries)? Thanks a lot for any help!! Klaus.

Dear R users, I used crr function in R package 'cmprsk' to fit a competing risks model. There were no any error or warning messages during running the function, but the output was obvious not correct. I saved the model fit as an object called f.crr. I extracted bfitj from the object by doing f.crr$bfitj, and found values of bfitj were extremely large (around 1e+138). I tried all

All, I am working with Emergency Department (ED) Length of Stay Data. The ED visit can end in one of a variety of ways (Admit, discharge, transfer, etc...) Initially, I have modeled the time to event by fitting a survival model to the time the outcome of interest and treat all other outcomes as censoring. However I recently came across the cmprsk package in R which seems to be developed

On 16/11/2017 4:53 PM, Boris Steipe wrote: > Large packages sometimes mask each other's functions and that creates a headache, especially for teaching code, since function signatures may depend on which order packages were loaded in. One of my students proposed using the idiom > > <function> <- <package>::<function> > > ... in a preamble, when we use

Dear R users, I am new to R and wanted to apply competing risk methods in my research work. I used the R code given by Zhang et al in his paper 'Nomogram for survival analysis in the presence of competing risks published in Ann Trans Med 2017:5(20):403. I am struggling with getting calibration curve thro' internal validation. I am happy to receive suggestion in the coding as well

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 folks Recently, I find that the number of the smbd connections may increase if the network is abnormal. And the repeated connections will exist for a long time (which is not accepted for me) So, I modify the following params and shorten the existing time of those repeated connections: TCP_KEEPCNT 3 TCP_KEEPIDLE 60 TCP_KEEPINTVL 15 My concern is that: Are there any

Hi all, I've been reading and using the information from the list for some time but this is my first question here. English is not my primary language, so sorry in advance for any language mistakes. :) I'm working with the "timereg" package to analize survival data. I want to perform a multivariate analisis of clinical information similar to the Cox regression but taking

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Hi R users, I'd like to draw a nomogram using a competing-risks regression (crr function in R), rather than a cox regression. However, the nomogram function provided in the Design package is not good for this purpose. Do you have any suggestion. I really appreciate your help Many thanks F.Abdollah, MD San-Raffele hospital Milan, Italy -- View this message in context: