R implementation of generalized survival models, where g(S(t|x))=eta(t,x) for a link function g, survival S at time t with covariates x and a linear predictor eta(t,x). The main assumption is that the time effect(s) are smooth. For fully parametric models with natural splines, this re-implements Stata's 'stpm2' function, which are flexible parametric survival models developed by Royston and colleagues. We have extended the parametric models to include any smooth parametric smoothers for time. We have also extended the model to include any smooth penalized smoothers from the 'mgcv' package, using penalized likelihood. These models include left truncation, right censoring, interval censoring, gamma frailties and normal random effects. This also includes a smooth implementation of accelerated failure time models.
|Author||Mark Clements [aut, cre], Xing-Rong Liu [aut], Paul Lambert [ctb]|
|Date of publication||2018-05-29 13:45:06 UTC|
|Maintainer||Mark Clements <[email protected]>|
|License||GPL-2 | GPL-3|
|Package repository||View on CRAN|
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