Function reference • flexsurv

Fitting survival models

flexsurvreg(): Flexible parametric regression for time-to-event data

flexsurvspline(): Flexible survival regression using the Royston/Parmar spline model.

flexsurvrtrunc(): Flexible parametric models for right-truncated, uncensored data defined by times of initial and final events.

survrtrunc(): Nonparametric estimator of survival from right-truncated, uncensored data

Getting results from survival models

summary(<flexsurvreg>): Summaries of fitted flexible survival models

standsurv(): Marginal survival and hazards of fitted flexsurvreg models

coef(<flexsurvreg>): Extract model coefficients from fitted flexible survival models

normboot.flexsurvreg(): Simulate from the asymptotic normal distribution of parameter estimates.

hr_flexsurvreg(): Hazard ratio as a function of time from a parametric survival model

vcov(<flexsurvreg>): Variance-covariance matrix from a flexsurvreg model

simulate(<flexsurvreg>): Simulate censored time-to-event data from a fitted flexsurvreg model

plot(<flexsurvreg>): Plots of fitted flexible survival models

lines(<flexsurvreg>): Add fitted flexible survival curves to a plot

plot(<standsurv>): Plot standardized metrics from a fitted flexsurv model

summary(<flexsurvrtrunc>): Summarise quantities of interest from fitted flexsurvrtrunc models

plot(<survrtrunc>) lines(<survrtrunc>): Plot nonparametric estimates of survival from right-truncated data.

Multi-state models based on transition-specific hazards

fmsm(): Construct a multi-state model from a set of parametric survival models

pars.fmsm(): Transition-specific parameters in a flexible parametric multi-state model

pmatrix.fs(): Transition probability matrix from a fully-parametric, time-inhomogeneous Markov multi-state model

pmatrix.simfs(): Transition probability matrix from a fully-parametric, semi-Markov multi-state model

totlos.fs(): Total length of stay in particular states for a fully-parametric, time-inhomogeneous Markov multi-state model

totlos.simfs(): Expected total length of stay in specific states, from a fully-parametric, semi-Markov multi-state model

sim.fmsm(): Simulate paths through a fully parametric semi-Markov multi-state model

simfs_bytrans(): Reformat simulated multi-state data with one row per simulated transition

bootci.fmsm(): Bootstrap confidence intervals for flexsurv output functions

pfinal_fmsm(): Probabilities of final states in a flexible parametric competing risks model

simfinal_fmsm(): Simulate and summarise final outcomes from a flexible parametric multi-state model

ajfit_fmsm(): Check the fit of Markov flexible parametric multi-state models against nonparametric estimates.

msfit.flexsurvreg(): Cumulative intensity function for parametric multi-state models

Competing risks and multi-state models based on mixtures

flexsurvmix(): Flexible parametric mixture models for times to competing events

get_basepars(): Evaluate baseline time-to-event distribution parameters given covariate values in a flexsurvmix model

mean_flexsurvmix(): Mean times to events from a flexsurvmix model

pdf_flexsurvmix(): Fitted densities for times to events in a flexsurvmix model

probs_flexsurvmix(): Probabilities of competing events from a flexsurvmix model

p_flexsurvmix(): Transition probabilities from a flexsurvmix model

quantile_flexsurvmix(): Quantiles of time-to-event distributions in a flexsurvmix model

rmst_flexsurvmix(): Restricted mean times to events from a flexsurvmix model

simt_flexsurvmix(): Simulate times to competing events from a mixture multi-state model

fmixmsm(): Constructor for a mixture multi-state model based on flexsurvmix

meanfinal_fmixmsm(): Mean time to final state in a mixture multi-state model

ppath_fmixmsm(): Probability of each pathway taken through a mixture multi-state model

qfinal_fmixmsm(): Quantiles of the distribution of the time until reaching a final state in a mixture multi-state model

ajfit(): Aalen-Johansen nonparametric estimates comparable to a fitted flexsurvmix model

ajfit_flexsurvmix(): Forms a tidy data frame for plotting the fit of parametric mixture multi-state models against nonparametric estimates

Model comparison and checking

logLik(<flexsurvreg>): Log likelihood from a flexsurvreg model

AICc(<flexsurvreg>) AICC(<flexsurvreg>): Second-order Akaike information criterion

AICc() AICC(): Second-order Akaike information criterion

BIC(<flexsurvreg>): Bayesian Information Criterion (BIC) for comparison of flexsurvreg models

AIC(<fmsm>): Akaike's information criterion from a flexible parametric multistate model

nobs(<flexsurvreg>): Number of observations contributing to a fitted flexible survival model

residuals(<flexsurvreg>): Calculate residuals for flexible survival models

coxsnell_flexsurvreg(): Cox-Snell residuals from a parametric survival model

Probability distributions

dsurvspline() psurvspline() qsurvspline() rsurvspline() Hsurvspline() hsurvspline() rmst_survspline() mean_survspline(): Royston/Parmar spline survival distribution

mean_survspline0() mean_survspline1() mean_survspline2() mean_survspline3() mean_survspline4() mean_survspline5() mean_survspline6() mean_survspline7() rmst_survspline0() rmst_survspline1() rmst_survspline2() rmst_survspline3() rmst_survspline4() rmst_survspline5() rmst_survspline6() rmst_survspline7() dsurvspline0() dsurvspline1() dsurvspline2() dsurvspline3() dsurvspline4() dsurvspline5() dsurvspline6() dsurvspline7() psurvspline0() psurvspline1() psurvspline2() psurvspline3() psurvspline4() psurvspline5() psurvspline6() psurvspline7() qsurvspline0() qsurvspline1() qsurvspline2() qsurvspline3() qsurvspline4() qsurvspline5() qsurvspline6() qsurvspline7() rsurvspline0() rsurvspline1() rsurvspline2() rsurvspline3() rsurvspline4() rsurvspline5() rsurvspline6() rsurvspline7() hsurvspline0() hsurvspline1() hsurvspline2() hsurvspline3() hsurvspline4() hsurvspline5() hsurvspline6() hsurvspline7() Hsurvspline0() Hsurvspline1() Hsurvspline2() Hsurvspline3() Hsurvspline4() Hsurvspline5() Hsurvspline6() Hsurvspline7(): Royston/Parmar spline survival distribution functions with one argument per parameter

dweibullPH() pweibullPH() qweibullPH() hweibullPH() HweibullPH() rweibullPH(): Weibull distribution in proportional hazards parameterisation

dgengamma() pgengamma() Hgengamma() hgengamma() qgengamma() rgengamma(): Generalized gamma distribution

dgengamma.orig() pgengamma.orig() Hgengamma.orig() hgengamma.orig() qgengamma.orig() rgengamma.orig(): Generalized gamma distribution (original parameterisation)

dgenf() pgenf() Hgenf() hgenf() qgenf() rgenf(): Generalized F distribution

dgenf.orig() pgenf.orig() Hgenf.orig() hgenf.orig() qgenf.orig() rgenf.orig(): Generalized F distribution (original parameterisation)

dgompertz() pgompertz() qgompertz() rgompertz() hgompertz() Hgompertz(): The Gompertz distribution

dllogis() pllogis() qllogis() rllogis() hllogis() Hllogis(): The log-logistic distribution

hexp() Hexp() hgamma() Hgamma() hlnorm() Hlnorm() hweibull() Hweibull(): Hazard and cumulative hazard functions

mean_exp() rmst_exp() mean_gamma() rmst_gamma() rmst_genf() mean_genf() rmst_genf.orig() mean_genf.orig() rmst_gengamma() mean_gengamma() rmst_gengamma.orig() mean_gengamma.orig() rmst_gompertz() mean_gompertz() mean_llogis() rmst_llogis() mean_lnorm() rmst_lnorm() mean_weibull() rmst_weibull() rmst_weibullPH() mean_weibullPH(): Mean and restricted mean survival functions

qgeneric(): Generic function to find quantiles of a distribution

Tools for using flexsurv with tidyverse

predict(<flexsurvreg>): Predictions from flexible survival models

tidy(<flexsurvreg>): Tidy a flexsurv model object

tidy(<standsurv>): Tidy a standsurv object.

augment(<flexsurvreg>): Augment data with information from a flexsurv model object

glance(<flexsurvreg>): Glance at a flexsurv model object

Datasets

bc: Breast cancer survival data

bos bosms3 bosms4: Bronchiolitis obliterans syndrome after lung transplants

Miscellaneous / advanced tools

model.frame(<flexsurvreg>) model.matrix(<flexsurvreg>): Extract original data from flexsurvreg objects.

model.frame(<flexsurvmix>): Model frame from a flexsurvmix object

basis(): Natural cubic spline basis

rmst_generic(): Generic function to find restricted mean survival time for some distribution

unroll.function(): Convert a function with matrix arguments to a function with vector arguments.

Package overview

flexsurv-package flexsurv: flexsurv: Flexible parametric survival and multi-state models