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survidm (version 1.3.2)

survidm-package: survidm: survidm

Description

Newly developed methods for the estimation of several probabilities in an illness-death model. The package can be used to obtain nonparametric and semiparametric estimates for: transition probabilities, occupation probabilities, cumulative incidence function and the sojourn time distributions. Additionally, it is possible to fit proportional hazards regression models in each transition of the Illness-Death Model. Several auxiliary functions are also provided which can be used for marginal estimation of the survival functions.

Arguments

References

Aalen O. O., Johansen S. (1978) An Empirical Transition Matrix for Nonhomogeneous Markov Chains Based on Censored Observations. Scandinavian Journal of Statistics, 5(3), 141--150.

Cao R., Lopez-de Ullibarri I., Janssen P., Veraverbeke N. (2005) Presmoothed kaplan-meier and nelsonaalen estimators. Journal of Nonparametric Statistics, 17, 31--56.

de Una-Alvarez J. and Meira-Machado L. (2015). Nonparametric estimation of transition probabilities in a non-Markov illness-death model: a comparative study. Biometrics, 71, 364--375.

Geskus R.B. (2011). Cause-specific cumulative incidence estimation and the fine and gray model under both left truncation and right censoring. Biometrics, 67, 39--49.

Meira-Machado L. F., de Una-Alvarez J. and Cadarso-Suarez C. (2006). Nonparametric estimation of transition probabilities in a non-Markov illness-death model. Lifetime Data Anal 12(3), 325--344.

Satten G.A. and Datta S. (2002) Marginal estimation for multi-stage models: waiting time distributions and competing risks analyses. Statistics in Medicine, 21, 3--19.