Markov chain Monte Carlo

Quantum mechanics

Bayesian probability

Statistics

Bivariate analysis

Event (particle physics)

Markov chain

Distribution (mathematics)

Computer science

Fraction (chemistry)

Physics

Organic chemistry

Mathematics

Econometrics

Block (permutation group theory)

Mathematical analysis

Confidence interval

Combinatorics

Chemistry

Posterior probability

Covariate

Journal of Applied Statistics

This paper presents estimates for the parameters included in the Block and Basu bivariate lifetime distributions in the presence of covariates and cure fraction, applied to analyze survival data when some individuals may never experience the event of interest and two lifetimes are associated with each unit. A Bayesian procedure is used to get point and confidence intervals for the unknown parameters. Posterior summaries of interest are obtained using standard Markov Chain Monte Carlo methods in rjags package for R software. An illustration of the proposed methodology is given for a Diabetic Retinopathy Study data set.

Block and Basu bivariate lifetime distribution in the presence of cure fraction