rstpm2

R implementation of generalized survival models (GSMs), smooth accelerated failure time (AFT) models and Markov multi-state models. For the GSMs, 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 doi:10.1177/0962280216664760. 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 doi:10.1002/sim.7451, and copulas. For the smooth AFTs, S(t|x) = S_0(t*eta(t,x)), where the baseline survival function S_0(t)=exp(-exp(eta_0(t))) is modelled for natural splines for eta_0, and the time-dependent cumulative acceleration factor eta(t,x)=\int_0^t exp(eta_1(u,x)) du for log acceleration factor eta_1(u,x). The Markov multi-state models allow for a range of models with smooth transitions to predict transition probabilities, length of stay, utilities and costs, with differences, ratios and standardisation.

Last 30 days

This package has been downloaded 8,008 times in the last 30 days. Impressive! The kind of number that makes colleagues ask, 'How did you do it?' The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 148 times.

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Last 365 days

This package has been downloaded 84,993 times in the last 365 days. The kind of number that gets mentioned in a keynote speech. Well done! The day with the most downloads was Aug 20, 2024 with 586 downloads.

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