RFmstate: Random Forest-Based Multistate Survival Analysis
Fits transition-specific cause-specific random survival forests
on a clock-reset duration scale for acyclic, non-recurrent multistate
processes. Entry-conditioned state-occupation probabilities are assembled
from predicted cumulative hazards by semi-Markov entry-mass and sojourn
convolution on a validated regular grid. The one-row-per-subject interface
supports one common initial state, one recorded entry per state, baseline
time-fixed covariates, competing exits, and independent right censoring.
Left truncation, recurrent visits, directed cycles, time-dependent
covariates, and ongoing-sojourn dynamic prediction are not supported.
The package also provides calendar-time Aalen-Johansen point estimates as
a covariate-free descriptive baseline, transition-specific permutation
importance, genuine ranger edge OOB concordance, and patient-level
cross-validated IPCW state-probability scoring. Methods are described in
Ishwaran et al. (2008) <doi:10.1214/08-AOAS169> for random survival
forests, Putter et al. (2007) <doi:10.1002/sim.2712> for multistate
competing risks decomposition, and Aalen and Johansen (1978)
<https://www.jstor.org/stable/4615704> for the nonparametric
estimator.
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