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...vents with terminal event: fitJoint<-frailtyPenal(Surv(time.entry,time.end,status)~cluster(id)+ terminal(status.terminal),formula.terminalEvent=~status.terminal,data=dataJoint ,n.knots=12,kappa1=1,kappa2=1,joint=TRUE,recurrentAG=TRUE) We included several examples. REFERENCES [1] Rondeau V, Michiels S, Liquet B, Pignon JP. Investigating trial and treatment hete rogeneity in an individual patient data meta-analysis of survival data by means of the penalized maximum likelihood approach. Statistics in Medicine 2008 ;27 :1894-1910. [2] Rondeau V, Mathoulin-Pelissier S, Jacqmin-Gadd...

...vents with terminal event: fitJoint<-frailtyPenal(Surv(time.entry,time.end,status)~cluster(id)+ terminal(status.terminal),formula.terminalEvent=~status.terminal,data=dataJoint ,n.knots=12,kappa1=1,kappa2=1,joint=TRUE,recurrentAG=TRUE) We included several examples. REFERENCES [1] Rondeau V, Michiels S, Liquet B, Pignon JP. Investigating trial and treatment hete rogeneity in an individual patient data meta-analysis of survival data by means of the penalized maximum likelihood approach. Statistics in Medicine 2008 ;27 :1894-1910. [2] Rondeau V, Mathoulin-Pelissier S, Jacqmin-Gadd...

...thing about using samba4 in a network with about 700 computers (mixed between WinXP, Vista, 7 and 2000) and about the same amount of users. Will it be stable enough? can I 'trust' samba for such network? Thanks a lot in advance! -- Horacio Agustin Lo Brutto horaciol at issecurity.com.ar Rondeau 2575 | Distrito Tecnol?gico | C.A.B.A ? Argentina M?vil: 54 9 11 6105 3898 | Tel. 54 11 4942 6877 www.issecurity.com.ar

Hello I would like to compare the results obtained with a classical non parametric proportionnal hazard model with a parametric proportionnal hazard model using a Weibull. How can we obtain the equivalence of the parameters using coxph(non parametric model) and survreg(parametric model) ? Thanks Virginie

Dear, I want to analyze two-level survival data using a shared frailty model, for which I want to use the R package 'Frailtypack", proposed by Rondeau et al. The dataset was built using SAS software. I also tried to change the format using SPSS and Excell. My (reduced) dataset has following column names: ID entry time status family var1 I used following command: > frailtyPenal(Surv(time, status) ~var1 + cluster(family), Fra...

Dear List, In documents (Therneau, 2003 : On mixed-effect cox models, ...), as far as I came to know, coxme penalize the partial likelihood (Ripatti, Palmgren, 2000) where as frailtyPenal (in frailtypack package) uses the penalized the full likelihood approach (Rondeau et al, 2003). How, then, coxme and coxph(...frailty(id, dist='gauss')) differs? Just the coding algorithm, or in approach too? coxph(...frailty(id, dist='gamma')) estimates by means of the penalized likelihood approach (Hougaard, 2000). Same for coxph(...frailty(id, dist='gaus...

Dear R users, We are pleased to tell you that "FRAILTYPACK" has been updated. "FRAILTYPACK" stands now for general frailty models estimated with a semi-parametrical penalized likelihood, but also with a parametrical approach. In case of comments/corrections/remarks/suggestions -- which are very welcome --please contact the maintainer directly. Kind regards, The

Dear R users, We are pleased to tell you that "FRAILTYPACK" has been updated. "FRAILTYPACK" stands now for general frailty models estimated with a semi-parametrical penalized likelihood, but also with a parametrical approach. In case of comments/corrections/remarks/suggestions -- which are very welcome --please contact the maintainer directly. Kind regards, The

A new version of the package FRAILTYPACK is now available on CRAN. -- possibility to fit now a Shared and a Joint Frailty model with a log-normal distribution for the random effects. -- possibility to deal with interval-censored data (for a shared frailty model) -- possibility to fit a joint frailty model for clustered data For more details see the corresponding NEWS files in the pkgs. We are

A new version of the package FRAILTYPACK is now available on CRAN. -- possibility to fit now a Shared and a Joint Frailty model with a log-normal distribution for the random effects. -- possibility to deal with interval-censored data (for a shared frailty model) -- possibility to fit a joint frailty model for clustered data For more details see the corresponding NEWS files in the pkgs. We are