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...= function() { 'returns the external pointer, regenerating if necessary' if (length(theta)) { if (.Call(isNullExtPtr, Ptr)) initializePtr() } Ptr }, ## ditto initializePtr = function() { Ptr <<- .Call(merPredDCreate, as(X, "matrix"), Lambdat, LamtUt, Lind, RZX, Ut, Utr, V, VtV, Vtr, Xwts, Zt, beta0, delb, delu, theta, u0) ... } merPredDCreate in turn just copies the relevant bits into a new C++ class object: /* see src/external.cpp */ SEXP merPredDCreate(SEXP Xs, SEXP Lambdat, SEXP LamtUt, SE...

...the development sample data I am able to get the probability of a event at time point(t). I need probability score of a event at specific time, using scoring scoring dataset which will have only covariates and not the response variables. Here is the sample code: n = 1000 beta1 = 2; beta2 = -1; lambdaT = .02 # baseline hazard lambdaC = .4 # hazard of censoring x1 = rnorm(n,0) x2 = rnorm(n,0) # true event time T = rweibull(n, shape=1, scale=lambdaT*exp(-beta1*x1-beta2*x2)) C = rweibull(n, shape=1, scale=lambdaC) #censoring time time = pmin(T,C) #observed time is min of censored and true even...

Hi, Does anyone know how to write a command to generate time-to-event data for Cox's regression?   Scomet [[alternative HTML version deleted]]

...on the scoring dataset, which will have only predictor information I am facing some issues. It would be great help for me if you tell me where am I going wrong! Here is the sample script! ######################################################### library(survival) n = 100 beta1 = 3; beta2 = -2; lambdaT = .01 lambdaC = .6 x1 = rnorm(n,0) x2 = rnorm(n,0) T = rweibull(n, shape=1, scale=lambdaT*exp(-beta1*x1-beta2*x2)) C = rweibull(n, shape=1, scale=lambdaC) time = pmin(T,C) event = time==T train_sample=data.frame(time,event,x1,x2) rm(time,event,x1,x2) fit_coxph <- coxph(Surv(tim...

..." "ussq" ... .. ..$ dims: Named int [1:12] 20 20 4 16 1 4 1 1 0 4 ... .. .. ..- attr(*, "names")= chr [1:12] "N" "n" "p" "nmp" ... ..@ pp :Reference class 'merPredD' [package "lme4"] with 18 fields .. ..$ Lambdat:Formal class 'dgCMatrix' [package "Matrix"] with 6 slots .. .. .. ..@ i : int [1:4] 0 1 2 3 .. .. .. ..@ p : int [1:5] 0 1 2 3 4 .. .. .. ..@ Dim : int [1:2] 4 4 .. .. .. ..@ Dimnames:List of 2 .. .. .. .. ..$ : NULL .. .. .. .. ..$ : NULL .. .. .. .....

Javier, Creo que aquí aplica la ley de Linus que dice: "Dado un número suficientemente elevado de ojos, todos los errores se convierten en obvios". La persona que revisa y encuentra un error no necesariamente tiene que ser la misma que la que lo escribe. Una motivación muy importante al compartir un código es la de recibir los beneficios del control de calidad por parte de tus pares.

...ot; ... > .. ..$ dims: Named int [1:12] 20 20 4 16 1 4 1 1 0 4 ... > .. .. ..- attr(*, "names")= chr [1:12] "N" "n" "p" "nmp" ... > ..@ pp :Reference class 'merPredD' [package "lme4"] with 18 fields > .. ..$ Lambdat:Formal class 'dgCMatrix' [package "Matrix"] with 6 slots > .. .. .. ..@ i : int [1:4] 0 1 2 3 > .. .. .. ..@ p : int [1:5] 0 1 2 3 4 > .. .. .. ..@ Dim : int [1:2] 4 4 > .. .. .. ..@ Dimnames:List of 2 > .. .. .. .. ..$ : NULL > .. .....