Prof Brian Ripley wrote: > The survival package is a recommended package in R and contains survreg() > which uses the AFT definitions for Weibull survival. This is well > documented, and MASS (the book) has comparisons of PH and AFT > parametrization for a Weibull example. > > I think you mean Frank Harrell's `Design' package. As far as I am aware > that has a function psm() (not PSM) which is based on survreg(), so the > interpretation should be the same.
Yes, at least until you run a psm Weibull fit through the pphsm convertor function. I recommend that Denis run the psm fit through Design's Hazard and Survival functions to create S functions containing the analytic representation of hazard and survival functions. There's also Mean and Quantile, and latex.psm. Frank > > On Fri, 26 Aug 2005, denis lalountas wrote: > > >>Hi to all, >>I am working on design package using survival function. >>First using PSM and adopting a weibull specification for the baseline hazard >>, I have got the following results(since weibull has both PH and AFT >>propreties ,in addition I have used the PPHSm command): >> >> Value Std. Error z p >> >>(Intercept) 1.768 1.0007 1.77 7.73e-02 >> >>SIZE -0.707 0.0895 -7.90 2.80e-15 >> >>REtoTA -0.896 0.4208 -2.13 3.33e-02 >> >>D1toEQ 0.281 0.0330 8.51 1.81e-17 >> >>EBTtoTA -6.706 1.0807 -6.21 5.46e-10 >> >>SALtoTA -3.943 0.3575 -11.03 2.78e-28 >> >>fishes 2.619 0.4194 6.24 4.26e-10 >> >>computers 2.781 0.2105 13.21 7.35e-40 >> >>Log(scale) -0.945 0.1514 -6.24 4.25e-10 >> >>and the loglikelihood -82.0 >> >>I dont know the specification of the weibull that Desing package uses so >>I can't evaluate the result. >> >>For comparison reasons I have estimated the same model using another >>spftware EasyReg >> >>wich gave the following results( the weibull specification has the form >>a(1).a(2).t^(a(2)-1): >> >>parameters ML estimate t-value p-value Covariates >> >>beta(1) 2.411460 2.136 0.03265 fishes >> >>beta(2) 2.710115 3.322 0.00089 computers >> >>beta(3) -7.539632 -2.646 0.00815 EBTtoTA >> >>beta(4) -3.720231 -2.547 0.01086 SALtoTA >> >>beta(5) 0.262115 1.982 0.04751 D1toEQ >> >>beta(6) -0.710535 -0.515 0.60684 REtoTA >> >>beta(7) -0.493369 -1.938 0.05262 LOG(SIZE) >> >>alpha(1) 0.485828 0.392 0.69491 >> >>alpha(2) 2.597073 5.516 0.00000 >> >>log(L)=-83,4 >> >>First observe that the results are almost the same but the weibull parameters >>are not. >> >>acooring to the weibull specification that easyreg uses a(2)>0 so the >>baseline hazard is monotonically increases ,acording to my expectations :(the >>empirical uncoditional hazard increases monotonically from t=1,12 and then >>decreases to zero) >> >>My question is what is the weibull specification that R-design package uses >>for the baseline hazard. Second ,it is possible to plot the baseline hazard >>in R , in order to "see" the accelerating-decelerating effect in the AFT case. >> >>In addition how can simulate a model in the AFT case ( some examples of >>simulation are given in the design manual for the COX-PH case. >> >>I hope that my questions are not borring, if so sory I am a new user of R >>package. >> >>Best regards >> >>D.Lalountas >> >>University of Patras , Greece >> >> >> >>--------------------------------- >> >> >> [[alternative HTML version deleted]] >> >>______________________________________________ >>[email protected] mailing list >>https://stat.ethz.ch/mailman/listinfo/r-help >>PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html >> > > -- Frank E Harrell Jr Professor and Chair School of Medicine Department of Biostatistics Vanderbilt University ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
