similar to: AFT model

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

Dear R-community, Dear Prof. Therneau, I would like to fit an AFT-model with time-dependent covariates and right-censored data. Searching the mailing list for information on the subject, I found some old posts which said it didn't work back then. My questions: (1) Has this kind of fitting already been implemented in the survival library in R? (2) If not: Are there any alternatives/

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

Hi all, I am trying to run Weibull PH model in R. Assume in the data set I have x1 a continuous variable and x2 a categorical variable with two classes (0= sick and 1= healthy). I fit the model in the following way. Test=survreg(Surv(time,cens)~ x1+x2,dist="weibull") My questions are 1. Is it Weibull PH model or Weibull AFT model? Call: survreg(formula = Surv(time, delta) ~ x1

Hi I have been having a rough time getting a Sangoma A200/Remora FXO/ FXS Analog AFT card set up properly. The main issue is that the card has four ports and as far as I can tell Asterisk is only seeing two. On the two that it recognizes the "Green" FXS ports are not green, they just are not lit. The "RED" FXO ports are indeed red, but from what I have read your not

Hello, I'm working with some left censored survival data using accelerated failure time models. I am interested in fitting different distributions to the data but seem to be getting the same results from the model fit using survreg regardless of the assumed distribution. These two codes seem to provide the same results: aft.gaussian <-

Hi to all, I am working on design package using survival function. First using PSM and adopting a weibull specification for the baseline hazard , I have got the following results(since weibull has both PH and AFT propreties ,in addition I have used the PPHSm command): Value Std. Error z p (Intercept) 1.768 1.0007 1.77 7.73e-02 SIZE -0.707 0.0895 -7.90 2.80e-15

I have fit an accelerated failure time model using coxph, and have what seems to be a simple question that I can't figure out. Given a vector of predictor values X, the survival time S[t|X] is the probability the entity will survive longer than some time t. Now, how do I calculate this for a specific value of t? -- View this message in context:

> I was wondering why survreg (in survival package) can not handle > three-way interactions. I have an AFT ..... You have given us no data to diagnose your problem. What do you mean by "cannot handle" -- does the package print a message "no 3 way interactions", gives wrong answers, your laptop catches on fire when you run it, ....? Also, make sure you read

Totally understood. If you remain "on vacation" (we wish eh?!) and get further messages like that from the list s'ware, just accept my standing apologies and delete them. Very welcome re letter! Very best, Chris ------- Forwarded message follows ------- Send reply to: "Alana O'C" <alanaoc at internode.on.net> From: "Alana O'C"

Hi all, I want to apply lasso method in AFT model. can anybody help me how to get lasso estimate using AFT model. Hossain [[alternative HTML version deleted]]

Hello, We are having issues with a NEW Sangoma A108D: -- Executing [691918892 at pbx1:1] Dial("SIP/xtravoip200-009d24b0", "DAHDI/g0/691918892|30|m") in new stack [Oct 1 10:04:43] WARNING[14171]: channel.c:3170 ast_request: No translator path exists for channel type DAHDI (native 76) to 256 [Oct 1 10:04:43] WARNING[14171]: app_dial.c:1237 dial_exec_full: Unable to create

Hi, I am trying to recreate the right graph on page 524 of Gelman's 2006 paper "Prior distributions for variance parameters in hierarchical models" in Bayesian Analysis, 3, 515-533. I am only interested, however, in recreating the portion of the graph for the overlain prior density for the half-Cauchy with scale 25 and not the posterior distribution. However, when I try:

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

Full_Name: Jörg Polzehl Version: 1.5.1 OS: Windows 2000 Submission from: (NULL) (193.175.148.198) When calculating MLE's in a variance component model using constrained optimization, i.e. optim(...,method="L-BFGS-B",...) I observed an inproper behaviour in cases where the likelihood function was evalueted at the constraint. Parameters and value of the function at the constraint

Hi, I'm using Sangoma's wanpipe together with dahdi, all software downloaded today at most recent version. Hardware is Sangoma A104, a 4xE1 card. Installation went well. Anyway, wanrouter status shows a different result than dahdi_tool or dahdi_scan. I've just put a hardware loop on port 1. All the other ports are open. wanrouter status shows the expected result: Device name |

Hello, I have following problem with Sangoma A104 card: CLI> pri show span 1 Primary D-channel: 16 Status: Provisioned, Down, Active Switchtype: EuroISDN Type: CPE Window Length: 0/7 Sentrej: 0 SolicitFbit: 0 Retrans: 0 Busy: 0 Overlap Dial: 0 T200 Timer: 1000 T203 Timer: 10000 T305 Timer: 30000 T308 Timer: 4000 T313 Timer: 4000 N200 Counter: 3 NOTICE[16509]: chan_zap.c:7494 pri_dchannel: PRI

Hi R lovers! I'd like to know how to use the parameter 'start' in the function fitdistr() obviously I have to provide the initial value of the parameter to optimize except in the case of a certain set of given distribution Indeed according to the help file for fitdistr " For the following named distributions, reasonable starting values will be computed if `start'

I have question (curiosity) regarding returned values of R's qcauchy () function, for nonexceedance probability (F). It seems the ideal returned range of cauchy distribution should be [-Inf,Inf]. For F=0 > qcauchy(0) [1] -Inf but for F=1 > qcauchy(1) [1] 8.16562e+15 It seems to me that the proper return value should be Inf??? For default (location=0,scale=1) quantile function of

Hi, I have A101DE Sangoma Card( http://www.sangoma.com/products/hardware_products/digital_voice_and_data_networking/a101.html ) lspci shows as 03:04.0 Network controller: Sangoma Technologies Corp. A200/Remora FXO/FXS Analog AFT card [root at asterisk ~]# lspci -vvv -s 03:04.0 03:04.0 Network controller: Sangoma Technologies Corp. A200/Remora FXO/FXS Analog AFT card Subsystem: Unknown device