search for: covarites

Dear all, I'm doing a survival analysis with time-dependent covariates. Until now, I have used a simple Cox model for this, specifically the coxph function from the survival library. Now, I would like to try out an accelerated failure time model with a parametric specification as implemented for example in the survreg function. Two questions: First, can survreg handle time-dependent

Hi, there, I have 5 datasets. I would like to choose a basis spline with same knots in GAM function in order to obtain same basis function for 5 datasets. Moreover, the basis spline is used to for an interaction of two covarites. I used "cr" in one covariate, but it can only smooth w.r.t 1 covariate. Can anyone give me some suggestion about how to choose a proper smoothing spline (bs='?') and knots for two covariates? Thanks a lot. Lee [[alternative HTML version deleted]]

...39;m trying to compute pairwise distances among pairs of observations, which each pair containing data from 2 groups. There are more than 100000 unique pairs. I have programmed a distance function that has three parameters, a vector of covariates from the ith observation in Group 1, a vector of covarites from the jth observation in Group 2, and a weighting matrix. I have used expand.grid to create a matrix containing all possible pairs of Keys (unique identifiers) from Group 1 and Group 2 and a placeholder for each pairwise distance in an effort to pre-allocate memory. The data containing the...

...ingular: reciprocal condition number = 1.28654e-24 This is obviously as a result of a problem with the data but apart from dataset a having 1674 rows and dataset b having 701 rows there is really no difference between them. The code I am using is as follows where covaea and covaeb are matrices of covarites, all coded as binary variables. In case a: > covaea <- cbind(sexa,fsha,fdra,nsigna,eega,th1a,th2a,stype1a,stype2a,stype3a,pgu1a,pgu2a,log(agea),firstinta/1000,totsezbasea) > fita <- crr(snearma$with.Withtime,csaea,covaea,failcode=2,cencode=0) and in case b: > covaeb <- cbind(sexb...

Dear R-help; I created a nlme model (Xnlme) with 3 fixed effects B1, B2, and B3. The random effects and available covariates in the groupedData were extracted with raned(): >Xnlme.ranef <- ranef(Xnlme, aug = T) When the fixed effect was plotted against covarites, an error occurred: >plot(Xnlme.ranef, form = B1 ~ ps + dr + el + sl + as) an error occurred: "Error in max(length(x0), length(x1), length(y0), length(y1)) : Argument "x0" is missing, with no default " Some of the covariates are factors (ps, dr, as) and some cont...

Dear All, Sorry if this question may not be appropriate to this list. I have the following question about the significance of effects in NLME. I fitted data with nlme using the SSlogis as a specification for the conditional mean of my dependent variable Y. When xmid and scal were considered as random, my covarite of interest X was found to have a significant effect on xmid but not on scal.

Dear friends, are there enough R users in Cyprus to form a club? jason Dr. Iasonas Lamprianou Department of Education The University of Manchester Oxford Road, Manchester M13 9PL, UK Tel. 0044 161 275 3485 iasonas.lamprianou at manchester.ac.uk ----- Original Message ---- From: "r-help-request at r-project.org" <r-help-request at r-project.org> To: r-help at r-project.org