| tteICE-package | tteICE: Treatment Effect Estimation for Time-to-Event Data with Intercurrent Events |
| bmt | Data from Section 1.3 of Klein and Moeschberger (1997) |
| plot.tteICE | Plot method for 'tteICE' objects |
| plot_ate | Plot estimated treatment effects |
| plot_inc | Plot estimated cumulative incidence functions (CIFs) |
| predict.tteICE | Predict method for 'tteICE' objects at specific time points |
| print.tteICE | Print method for 'tteICE' objects |
| scr.composite | Fit CIFs using composite variable strategy for semicompeting risks data |
| scr.composite.eff | Fit CIFs using composite variable strategy for semicompeting risks data, based on efficient influence functions |
| scr.natural | Fit CIFs using hypothetical strategy (I) for semicompeting risks data |
| scr.natural.eff | Fit CIFs using hypothetical strategy (I) for semicompeting risks data, based on efficient influence functions |
| scr.principal | Fit CIFs using principal stratum strategy for semicompeting risks data |
| scr.principal.eff | Fit CIFs using principal stratum strategy for semicompeting risks data, based on efficient influence functions |
| scr.removed | Fit CIFs using hypothetical strategy (II) for semicompeting risks data |
| scr.removed.eff | Fit CIFs using hypothetical strategy (II) for semicompeting risks data, based on efficient influence functions |
| scr.treatment | Fit CIFs using treatment policy strategy for semicompeting risks data |
| scr.treatment.eff | Fit CIFs using treatment policy strategy for semicompeting risks data, based on efficient influence functions |
| scr.tteICE | Fit CIFs for semicompeting risks time-to-event data with intercurrent events. |
| scr.whileon | Fit CIFs using while on treatment strategy for semicompeting risks data |
| scr.whileon.eff | Fit CIFs using while on treatment strategy for semicompeting risks data, based on efficient influence functions |
| summary.tteICE | Summary method for 'tteICE' objects |
| surv.boot | Calculate standard errors for estimated CIFs and treatment effects |
| surv.composite | Fit CIFs using composite variable strategy for competing risks data |
| surv.composite.eff | Fit CIFs using composite variable strategy for competing risks data, based on efficient influence functions |
| surv.HR | Estimate hazard ratios |
| surv.natural | Fit CIFs using hypothetical strategy (I) for competing risks data |
| surv.natural.eff | Fit CIFs using hypothetical strategy (I) for competing risks data, based on efficient influence functions |
| surv.principal | Fit CIFs using principal stratum strategy for competing risks data |
| surv.principal.eff | Fit CIFs using principal stratum strategy for competing risks data, based on efficient influence functions |
| surv.removed | Fit CIFs using hypothetical strategy (II) for competing risks data |
| surv.removed.eff | Fit CIFs using hypothetical strategy (II) for competing risks data, based on efficient influence functions |
| surv.treatment | Fit CIFs using treatment policy strategy for competing risks data |
| surv.treatment.eff | Fit CIFs using treatment policy strategy for competing risks data, based on efficient influence functions |
| surv.tteICE | Fit CIFs for competing risks time-to-event data with intercurrent events. |
| surv.whileon | Fit CIFs using while on treatment strategy for competing risks data |
| surv.whileon.eff | Fit CIFs using while on treatment strategy for competing risks data, based on efficient influence functions |
| tteICE | Using formula to fit CIFs for time-to-event data with intercurrent events |
| tteICEShiny | Shiny app for tteICE |