Journal ArticleDOI
Dynamic lifetime prediction using a Weibull-based bivariate failure time model: a meta-analysis of individual-patient data
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In this article, a dynamic prediction method using a bivariate failure time model allows one to build a prediction for the time-to-death for patients, which is one of the most important issues in survival analysis.Abstract:
Predicting time-to-death for patients is one of the most important issues in survival analysis. A dynamic prediction method using a bivariate failure time model allows one to build a prediction for...read more
Citations
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A copula-based Markov chain model for serially dependent event times with a dependent terminal event
TL;DR: This paper proposes a novel copula-based Markov chain model for describing serial dependence in recurrent event times, and proposes a two-stage estimation method under Weibull distributions for fitting the survival data.
Journal ArticleDOI
Parametric Distributions for Survival and Reliability Analyses, a Review and Historical Sketch
TL;DR: In this paper , the authors comprehensively review the historical backgrounds and statistical properties of a number of parametric distributions used in survival and reliability analyses, including the exponential, Weibull, Rayleigh, lognormal, log-logistic, gamma, generalized gamma, Pareto (types I, II, and IV), Hjorth, Burr (types III and XII), Dagum, exponential power, Gompertz, Birnbaum-Saunders, exponential-logarithmic, piecewise exponential, generalized exponential, exponentiated Weibell, generalized modified Weibbull, and spline distributions.
Journal ArticleDOI
A recursive method for the health assessment of systems using the proportional hazards model
TL;DR: In this paper , the authors developed a novel recursive method to approximately assess the health indices of the proportional hazards model with a Markovian covariate process, which discretizes age into equidistant and small subintervals, and constructs an incomplete state transition matrix with each element measured by its upper and lower bounds.
Journal ArticleDOI
Likelihood analysis and stochastic EM algorithm for left truncated right censored data and associated model selection from the Lehmann family of life distributions
TL;DR: In this paper, a study of model selection based on left truncated right censored data from the Lehmann family of distributions is carried out through extensive Monte Carlo simulations, and performances of the inferential methods are examined.
Journal ArticleDOI
Zero-inflated-censored Weibull and gamma regression models to estimate wild boar population dispersal distance
Eduardo de Freitas Costa,Silvana Schneider,Giulia Bagatini Carlotto,Tainá Cabalheiro,Mauro Ribeiro de Oliveira Júnior +4 more
TL;DR: Two different zero-inflated-right-censored regression models, assuming Weibull and gamma distributions are proposed, and it is shown that the models were useful to extract inferences about the wild boar dispersal, correctly describing the data mimicking a situation where males disperse more than females, and age has a positive effect on the dispersal of theWild boar’s population.
References
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Journal ArticleDOI
Monotone Regression Splines in Action
TL;DR: In this article, the authors show the virtues of monotone splines through a number of statistical applications, including response variable transformation in nonlinear regression, transformation of variables in multiple regression, principal components and canonical correlation.
Journal ArticleDOI
Consistent Estimation of the Expected Brier Score in General Survival Models with Right-Censored Event Times
TL;DR: It is shown that a modified version of this estimator is consistent even when censoring and event times are only conditionally independent given the covariates, and is derived on the basis of regression models for the censoring distribution.
Journal ArticleDOI
A Three-Gene Model to Robustly Identify Breast Cancer Molecular Subtypes
Benjamin Haibe-Kains,Christine Desmedt,Sherene Loi,Aedín C. Culhane,Gianluca Bontempi,John Quackenbush,Christos Sotiriou +6 more
TL;DR: The results suggest that adequate classification of the major and clinically relevant molecular subtypes of breast cancer can be robustly achieved with quantitative measurements of three key genes.
Book
Dynamic Prediction in Clinical Survival Analysis
TL;DR: Aimed at applied statisticians who actively analyze clinical data in collaboration with clinicians, the analyses of the different data sets throughout the book demonstrate how predictive models can be obtained from proper data sets.