survival parametric question
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]]
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Frank E Harrell Jr Professor and Chair School of Medicine
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