Presmoothed Landmark Aalen-Johansen Estimator of Transition Probabilities for complex multi-state models.

presmoothedTP is an R package which extends the landmark Aalen-Johansen estimator by incorporating presmoothing techniques, offering a robust alternative for estimating transition probabilities in non-Markovian multi-state models with multiple states and potential reversible transitions.

InstallationIf you want to use the release version of the presmoothedTP package, you can install the package from CRAN as follows: install.packages(pkgs="presmoothedTP");

Authors Gustavo Soutinho and Luís Meira-Machado lmachado@math.uminho.pt Maintainer: Gustavo Soutinho gustavosoutinho@sapo.pt

Funding This work was suported by the UIDB/05105/2020 Program Contract, funded by funds through the FCT I.P.

References Aalen, O., Johansen, S. An empirical transition matrix for non homogeneous markov and chains based on censored observations. Scandinavian Journal of Statistics, 5:141–150; 1978. Andersen, P. K., Borgan, Ø., Gill, R. D., Keiding,N. Statistical Models Based on Counting Processes. Springer-Verlag, New York; 1993. Byar, D. P. The Veterans Administration study of chemoprophylaxis for recurrent stage I bladder tumors: comparisons of placebo, pyridoxine and topical thiotepa. In Bladder Tumors and Other Topics in Urological Oncology, Edited by M. Pavone-Macaluso, P. H. Smith and F. Edsmyr, Plenum, 363–370, Springer, New York; 1980.

Datta, S., Satten, G. Validity of the aalen-johansen estimators of stage occupation probabilities and nelson aalen integrated transition hazards for non-markov models. Statistics & Probability Letters, 55: 403–411; 2001. de U˜na- ´Alvarez, J., Meira-Machado, L. Nonparametric estimation of transition probabilities in the non-markov illness-death model: A comparative study. Biometrics, 71(2):364–375; 2015. Nießl, A., Allignol, A., Beyersmann, J., Mueller, C. Statistical inference for state occupation and transition probabilities in non-Markov multi-state models subject to both random left-truncation and right-censoring, Econometrics and Statistics, 25; 2023. Putter, H., Fiocco, M., Geskus, R. B. Tutorial in biostatistics: Competing risks and multistate models. Statistics in Medicine, 26(11):2389–2430; 2007. Putter, H., Spitoni, C. Non-parametric estimation of transition probabilities in nonmarkov multistate models: The landmark aalen-johansen estimator. Statistical Methods in Medical Research, 27:2081–2092; 2018. Van Houwelingen, H. C. Dynamic prediction by landmarking in event history analysis. Scandinavian Journal of Statistics, 34(1):70–85; 2007. Soutinho, G., Meira-Machado, L., Oliveira, P. A comparison of presmoothing methods in the estimation of transition probabilities. Communications in Statistics - Simulation and Computation, 51(9): 5202–5221; 2020. Soutinho, G., Sestelo, M., Meira-Machado, L. survidm: An R package for Inference and Prediction in an Illness-Death Model. The R Journal, 13(2):70–89; 2021. R Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria; 2021.