search for: covarit

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 th...

...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(se...

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 co...

...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. However, when I assume that only xmid is random, the effect of my covariate X was found to have a significant effect on both xmid and scal. Of course the AIC and the residuals were both smaller in the firts model. Thus m...

...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. However, when I assume that only xmid is random, the effect of my covariate X was found to have a significant effect on both xmid and scal. Of course the AIC and the residuals were both smaller in the firts model. Thus m...