discSurv-package: Discrete Survival Analysis

Description

Includes functions for data transformations, estimation, evaluation and simulation of discrete survival analysis. Also discrete life table estimates are available. The most important functions are listed below:

contToDisc:

{Discretizes continuous time variable into a specified grid of censored data for discrete survival analysis.} dataLong:{Transform data from short format into long format for discrete survival analysis and right censoring.} dataLongCompRisks:{Transforms short data format to long format for discrete survival modelling in the case of competing risks with right censoring.} dataLongTimeDep:{Transforms short data format to long format for discrete survival modelling of single event analysis with right censoring.} concorIndex:{Calculates the concordance index for discrete survival models (independent measure of time).} simCompRisk:{Simulates responses and covariates of discrete competing risk models.}

Arguments

Details

ll{ Package: discSurv Type: Package Version: 1.1.2 Date: 2015-11-07 License: GPL-3 }

References

Gerds T. A. and M. Schumacher, (2006), Consistent estimation of the expected Brier score in general survival models with right-censored event times, Biometrical Journal 48(6), 1029-1040 Gerhard Tutz, (2012), Regression for Categorical Data, Cambridge University Press Hajime Uno and Tianxi Cai and Lu Tian and L. J. Wei, (2007), Evaluating Prediction Rules for t-Year Survivors With Censored Regression Models, Journal of the American Statistical Association Jerald F. Lawless, (2000), Statistical Models and Methods for Lifetime Data, 2nd edition, Wiley series in probability and statistics Ludwig Fahrmeir, (1997), Discrete failure time models, LMU Sonderforschungsbereich 386, Paper 91, http://epub.ub.uni-muenchen.de/ Patrick J. Heagerty and Yingye Zheng, (2005), Survival Model Predictive Accuracy and ROC Curves, Biometrics 61, 92-105 Roger B. Nelsen, (2006), An introduction to Copulas, Springer Science+Business Media, Inc. Steele Fiona and Goldstein Harvey and Browne William, (2004), A general multilevel multistate competing risks model for event history data Statistical Modelling, volume 4, pages 145-159 Tilmann Gneiting and Adrian E. Raftery, (2007), Strictly proper scoring rules, prediction, and estimation, Journal of the American Statistical Association 102 (477), 359-376 Van der Laan M. J. and J. M. Robins, (2003), Unified Methods for Censored Longitudinal Data and Causality, Springer, New York W. A. Thompson Jr., (1977), On the Treatment of Grouped Observations in Life Studies, Biometrics, Vol. 33, No. 3 Wiji Narendranathan and Mark B. Stewart, (1993), Modelling the probability of leaving unemployment: competing risks models with flexible base-line hazards, Applied Statistics, pages 63-83 William H. Kruskal, (1958), Ordinal Measures of Association, Journal of the American Statistical Association, Vol. 53, No. 284, pp. 814-861