search for: coxpath

Hi, I am new to model selection by coefficient shrinkage method such as lasso. And I became particularly interested in variable selection in Cox regression by lasso. I became aware of the coxpath() in R package glmpath does lasso on Cox model. I have tried the sample script on the help page of coxpath(), but I have difficult time understanding the output. Therefore, I would greatly appreciate if anyone can help me understand how to use the function. > data(lung.data) > attach(lung.da...

We have uploaded to CRAN a new version of glmpath, a package which fits the L1 regularization path for generalized linear models. The revision includes: - coxpath, a function for fitting the L1-regularization path for the Cox ph model; - bootstrap functions for analyzing sparse solutions; - the ability to mix in L2 regularization along with L1 (elasticnet). We have also completed a report that describes these methods in detail: http://www-stat.stanford.edu...

We have uploaded to CRAN a new version of glmpath, a package which fits the L1 regularization path for generalized linear models. The revision includes: - coxpath, a function for fitting the L1-regularization path for the Cox ph model; - bootstrap functions for analyzing sparse solutions; - the ability to mix in L2 regularization along with L1 (elasticnet). We have also completed a report that describes these methods in detail: http://www-stat.stanford.edu...

Hi, I am analyzing a set of variables in order to create a survival model for a set of patients. I have checked the reference manual for glm path and coxpath in order to achieve it. However I have a doubt about the class of the covariates I can use with the last mentioned package. In the example, the package loads a list called "lung.data". This object has a matrix with the covariate information "x" and two vectors about the censori...

Hi all, I'm relatively new to using R, and have been trying to fit an L1 regularization path using coxpath from the glmpath library. I'm interested in using a cross validation framework, where I crossvalidate on a training set to select the lambda that achieves the lowest error, then use that value of lambda on the entire training set, before applying to a test set. This seems to entail somehow us...

...mpath 0.94. My version happens to give a more clear example of a problem than the original one. Lines 86-89 of glmpath-Ex.R: bootstrap.a <- bootstrap.path(heart.data$x, heart.data$y, B=10, method="bic") ## End Don't show bootstrap.a Lines 130-133 of glmpath-Ex.R: ### Name: cv.coxpath ### Title: Computes cross-validated (minus) log-partial-likelihoods for ### coxpath ### Aliases: cv.coxpath The end of glmpath-Ex.Rout: > bootstrap.a <- bootstrap.path(heart.data$x, heart.data$y, + B=10, method="bic") > al-likelihoods for Error: unexpected 'for' i...

...cox model with the following syntax: # cox01def <-cph(Surv(TEVENT,EVENT) ~ ifelse(AGE>50, (AGE-50)^2,0) + BMI + # HDL+DIABETES +HISTCAR2 + log(CREAT)+ as.factor(ALBUMIN)+STENOSIS+IMT,data # = XC, x=T, y=T, surv=T) *1 Furthermore I have estimated my beta's also with a Lasso method - Coxpath ( from Glmpath pckage) , namely: # LASSOdata <- list(x=cox01$x, time=XC$TEVENT, status=XC$EVENT) # summary(LASSOdata) # LASSOpath <- coxpath(data=SMARTdata) My problem is the following: I want to make a nomogram with the beta's from the lasso. Is that possible? I know of the nomogram-...

...id where for one single patient, the answer is "NULL". Could anyone help me with the problem? R.app GUI 1.34 (5589 Leopard build 32-bit) > library(glmpath) *> dataall <- list(x=lung.data$x[1:130,], time=lung.data$time[1:130], status=lung.data$status[1:130])* * > fit.a <- coxpath(dataall) > testall <- list(x=lung.data$x[131:137,], time=lung.data$time[131:137], status=lung.data$status[131:137]) > testpred <- predict(fit.a, testall, s=0.99, type='coxph', mode='lambda.fraction') > testpred Call: coxph(formula = Surv(time, status) ~ x, metho...

...id where for one single patient, the answer is "NULL". Could anyone help me with the problem? R.app GUI 1.34 (5589 Leopard build 32-bit) > library(glmpath) *> dataall <- list(x=lung.data$x[1:130,], time=lung.data$time[1:130], status=lung.data$status[1:130])* * > fit.a <- coxpath(dataall) > testall <- list(x=lung.data$x[131:137,], time=lung.data$time[131:137], status=lung.data$status[131:137]) > testpred <- predict(fit.a, testall, s=0.99, type='coxph', mode='lambda.fraction') > testpred Call: coxph(formula = Surv(time, status) ~ x, metho...

...> ? 24. Re: Converting date format (Nutter, Benjamin) > ? 25. Solutions for memory problems (packages ff, > bigmemory)? > ? ? ? (hhafner at statistik-hessen.de) > ? 26. multi-stage sampling and hierarchical models: > which packages? > ? ? ? (Steve Powell) > ? 27. glmpath and coxpath variables (Antoni > Picornell) > ? 28. using a list to index elements of a list > (Pj253) > ? 29. Re: using a list to index elements of a list > (Benilton Carvalho) > ? 30. Re: using a list to index elements of a list > (Pj253) > ? 31. Re: using a list to index elements of a...

...cox model with the following syntax: # cox01def <-cph(Surv(TEVENT,EVENT) ~ ifelse(AGE>50, (AGE-50)^2,0) + BMI + # HDL+DIABETES +HISTCAR2 + log(CREAT)+ as.factor(ALBUMIN)+STENOSIS+IMT,data # = XC, x=T, y=T, surv=T) *1 Furthermore I have estimated my beta's also with a Lasso method - Coxpath ( from Glmpath pckage) , namely: # LASSOdata <- list(x=cox01$x, time=XC$TEVENT, status=XC$EVENT) # summary(LASSOdata) # LASSOpath <- coxpath(data=SMARTdata) My problem is the following: I want to make a nomogram with the beta's from the lasso. Is that possible? I know of the nomogram-...