similar to: eha aftreg overall p-value

Dear R-users, I need to use the aftreg function in package 'eha' to estimate failure times for left truncated survival data. Apparently, survreg still cannot fit such models. Both functions should be fitting the accelerated failure time (Weibull) model. However, as G?ran Brostr?m points out in the help file for aftreg, the parameterisation is different giving rise to different

G?ran, thanks for the update, I'm just about to install it! Just wanted to drop you a short line about performance (as you once requested): aftreg takes ages on my windows machine to calculate a small set of 7 observations which are not even grouped together by "id". To be a bit more precise, it takes 2:40 mins on my Intel T9300 Core2 Duo @ 2.5 GHz. Bigger samples with about 700

Dear R-community, I have a short question: How do I interpret the result of a likelihood ratio test correctly? I am fitting a parametric survival model (with aftreg {eha}) and the output tells me the overall p-value of my model is < 0.001. My simple question is: Does the result mean my model fits the data well OR does it mean my model DOES NOT fit the data well? Some side information how the

This kind of error seems to surprise R users. It surprises me that it doesn't happen much more frequently. The "BFGS" method of optim() from the 1990 Pascal version of my book was called the Variable Metric method as per Fletcher's 1970 paper it was drawn from. It really works much better with analytic gradients, and the Rvmmin package which is an all-R version that adds bounds

Hi list! I'm getting an error message when trying to fit an accelerated failure time parametric model using the aftreg() function from package eha: > Error in optim(beta, Fmin, method = "BFGS", control = list(trace = > as.integer(printlevel)), : > non-finite finite-difference value [2] This only happens when adding four specific covariates at the same time in the

I am unsure what is being returned, and what is supposed to be returned, when using 'predict' with "type='expected'" for an aftreg survival model. The code below first generates a weibull model, then uses predict to create a vector of the linear predictors, then attempts to create the 'expected' vector, which is empty. The final two steps in the code generate a

Dear all, I have some trouble using the "id"-argument with aftreg (accelerated failure time regression analysis from the eha library). As far as I understand it, the id argument is used to group individuals together if there are time-varying covariates and the data is arranged in counting process style. Unfortunately, i cannot figure out how to use the "id"-argument. The

Dear all, does anyone know how I can extract specific p-values for covariates from an aftreg object? After fitting a model with aftreg I can find all different variables by using str(), but there's no place where p-values are kept. The odd thing is that print() displays them correctly. EXAMPLE: > testdata start stop censor groupvar var1 var2 1 0 1 0

Hi, I'm estimating a loglogistic aft (accelerated failure time) model, just a simple plain vanilla one (without time dependent covariates), I'm comparing the results that I obtain between aftreg (eha package) and survreg(surv package). If I don't use any covariate the results are identical , if I add covariates all the coefficients are the same until a precision of 10^4 or 10^-5 except

A few days ago I uploaded to CRAN a new package called 'eha', which stands for 'Event History Analysis'. Its main focus is on proportional hazards modeling in survival analysis, and in that respect eha can be regarded as a complement and an extension to the 'survival' package. In fact eha requires survival. Eha contains three functions for proportional hazards

A few days ago I uploaded to CRAN a new package called 'eha', which stands for 'Event History Analysis'. Its main focus is on proportional hazards modeling in survival analysis, and in that respect eha can be regarded as a complement and an extension to the 'survival' package. In fact eha requires survival. Eha contains three functions for proportional hazards

Hello, I am apparently confused about the use of an id parameter for an event history/survival model, and why the EHA documentation for aftreg does not specify one. All assistance and insights are appreciated. Attempting to specifiy an id variable with the documentation example generates an "overlapping intervals" error, so I sorted the original mort dataframe and set subsequent entry

Dear R-users, I have two samples with individuals that are in more than one of the samples and individuals that are only in one sample. I have been trying to do a pooled hazard model, stacking one sample below the other, with aftreg and time-dependent covariates. The idea behind is to see aggregate effects of covariates, but need to control for ther effects of same individuals in both samples

A new version of 'eha' (0.92-1) is now on CRAN. From the ChangeLog: 0.92-1 (January 7, 2004) * mlreg: Geometric distribution (i.e., constant baseline discrete hazard) added. Not for frailty models, yet (on the TODO list). * mlreg: New argument, 'n.points', added to 'control'. Controls the number of points used in the Gauss-Hermite quadrature. * mlreg: Stricter

A new version (0.96.3) of the package 'eha' is now on CRAN. Apart from some bug fixes, there are some news. The most noteworthy are: (i) 'plot.Surv' has a few new options, (ii) 'weibreg' now can fit null models (i.e., only scale and shape) and covariates are no longer automatically centered (although this is still the default), (iii) there is a new function,

A new version of 'eha' (0.92-1) is now on CRAN. From the ChangeLog: 0.92-1 (January 7, 2004) * mlreg: Geometric distribution (i.e., constant baseline discrete hazard) added. Not for frailty models, yet (on the TODO list). * mlreg: New argument, 'n.points', added to 'control'. Controls the number of points used in the Gauss-Hermite quadrature. * mlreg: Stricter

Dear Prof. Brostr?m, Dear R-mailinglist, first of all thanks a lot for your great effort to incorporate time-varying covariates into aftreg. It works like a charm so far and I'll update you with detailled benchmarks as soon as I have them. I have one more questions regarding Accelerated Failure Time models (with aftreg): You mention that left truncation in combination with time-varying

On Wed, Aug 1, 2012 at 3:08 PM, <fra.meucci@hotmail.it> wrote: > Dear Göran Broström, > I am trying to use AFTREG function for R to estimate a loglogistic > survival function, including time dependent covariates. > Actually, my Subset includes some partial events; the idea is to model > this kind of events using something similar to “weights” in the SURVREG > function.

When I try 'install-packages' (from menu) in R-1.7.0 (Windows), I get > install.packages(choose.files('',filters=Filters[c('zip','All'),]), .libPaths()[1], CRAN = NULL) Error in file(file, "r") : unable to open connection In addition: Warning message: cannot open file `eha060/DESCRIPTION' > but it works with R-1.6.2. It also works if I

Now I try to add some C and Fortan code to my package, so the NAMESPACE file is useDynLib(eha) importFrom(survival, Surv) export(mlreg.fit, risksets) but I get ..... * checking R files for library.dynam ... OK * checking S3 generic/method consistency ... WARNING Error in .try_quietly({ : Error in library(package, lib.loc = lib.loc, character.only = TRUE, verbose = FALSE) :