Modeling Survival Data Using Frailty Models. - 2nd. Edition. - Symbiosis International University Pune, Maharashtra, India | Springer Nature Singapore Pte Ltd | 2019. - 307 Pages Includes References and Index. - Industrial and Applied Mathematics. .


This book presents the basic concepts of survival analysis and frailty models, covering both fundamental and advanced topics. It focuses on applications of statistical tools in biology and medicine, highlighting the latest frailty-model methodologies and applications in these areas. After explaining the basic concepts of survival analysis, the book goes on to discuss shared, bivariate, and correlated frailty models and their applications. It also features nine datasets that have been analyzed using the R statistical package. Covering recent topics, not addressed elsewhere in the literature, this book is of immense use to scientists, researchers, students and teachers.

ISBN: 978-981-15-1180-6 978-981-15-1181-3 (eBook)

ISSN: 2364-6837 2364-6845 (electronic) = Modeling Survival Data Using Frailty Models. AIC algorithm analyze Australian twin data autocorrelation based on reversed baseline distribution baseline hazard Bayes factor BIC bivariate survival data bivariate survival function Burn-in period censored convergence correlated frailty model covariates data for Model data set Model diabetic retinopathy diabetic retinopathy data Eq exp failure rate Fig frailty distribution frailty models based frailty variable gamma distribution gamma frailty model Gaussian frailty models Gelman Geweke test given Hanagal hazard function heterogeneity ho(t Hougaard inverse Gaussian frailty Iteration number kidney infection data Laplace transform likelihood function log-logistic distribution loglikelihood lognormal Markov chain Model G-III Model IG-I Model RH-II multivariate p-values patients positive stable frailty Posterior summary proportional hazards model random effect random variable regression model reversed hazard rate running mean plots sample scale parameter shared frailty models Stat statistic summary for Australian survival analysis survival function Table twin data set variance Weibull distribution α β βι γ θ λι ν ρ σ

Subjects--Personal Names: --Biometry, Computer simulation, Computers / Computer Simulation, Mathematics / Probability & Statistics / Bayesian Analysis, Mathematics / Probability & Statistics / General, Medical / Biostatistics, Medical / General, Statistics, Bayesian Inference, Failure time data analysis -- Mathematical models, Simulation and Modeling, Statistics for Life Sciences, Medicine, Health Sciences, Survival analysis (Biometry) -- Mathematical models.