logo survival analysis prop. hazard model shared frailty model Simulation discussion Procedures for analyzing Frailty-Models in SAS and R Katharina Hirsch Martin-Luther-Universit¨ at Halle-Wittenberg Institut f¨ ur Medizinische Epidemiologie, Biometrie und Informatik 20.11.2009 Katharina Hirsch Frailty-Models 20.11.2009 1 / 23
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Procedures for analyzing Frailty-Models in SAS and R · 2010-01-31 · Procedures for analyzing Frailty-Models in SAS and R Katharina Hirsch Martin-Luther-Universit at Halle-Wittenberg
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survival analysis prop. hazard model shared frailty model Simulation discussion
Procedures for analyzing Frailty-Models in SAS and R
Katharina Hirsch
Martin-Luther-Universitat Halle-WittenbergInstitut fur Medizinische Epidemiologie, Biometrie und Informatik
20.11.2009
Katharina Hirsch Frailty-Models 20.11.2009 1 / 23
logo
survival analysis prop. hazard model shared frailty model Simulation discussion
outline
1 survival analysis
2 proportional hazard model
3 shared frailty model
4 Simulation
5 discussion
Katharina Hirsch Frailty-Models 20.11.2009 2 / 23
logo
survival analysis prop. hazard model shared frailty model Simulation discussion
survival data
observation of single events
discharge from the hospitaldisruption of materialonset of a disease
analyzing the event time
estimation of the effect of prognostic factors
often censored data:
end of the studylost to follow-upcompeting risk
Katharina Hirsch Frailty-Models 20.11.2009 3 / 23
logo
survival analysis prop. hazard model shared frailty model Simulation discussion
survival analysis prop. hazard model shared frailty model Simulation discussion
Literature
D.R. Cox: Regression models and life tables. Journal of the RoyalStatistical Society 34, 187 – 202, 1972.L. Duchateau, P. Janssen: The Frailty Model. Springer New York, 2008.H. T. V. Vu und M. W. Knuiman: A hybrid ML-EM algorithm forcalculation of maximum likelihood estimates in semiparametric shared frailtymodels. Computational Statistics & Data Analysis, 40(1), 173 – 187, 2002.H. Vu, M. Segal, M. Knuiman and I. James: Asymptotic and smallsample statistical properties of random frailty variance estimates for sharedgamma frailty models. Communication in Statistics: Simulation andComputation30(3), 581 – 595, 2001.V. Rondeau and J. R. Gonzalez: frailtypack:A computer program for theanalysis of correlated failure time data using penalized likelihood estimation.Computer Methods and Programs in Biomedicine 80, 154 – 164, 2005.G. Kauermann and R. Xu and F. Vaida: Stacked Laplace-EMalgorithm for duration models with time-varying and random effects.Computational Statistics and Data Analysis 52, 2514 – 2528, 2008.R Development Core Team: The R project for statistical computing.URL: http://www.r-project.org, 2008.