The objective of Lifetime Data Analysis is to advance and promote statistical science in the various applied fields that deal with lifetime data, including: Actuarial Science  Economics  Engineering Sciences  Environmental Sciences  Management Science  Medicine  Operations Research  Public Health  Social and Behavioral Sciences. The following listing of some current topics of interest to the journal is not intended to be exclusive but to indicate the editorial policy of attracting papers generated by a broad range of interests: accelerated failure time models  Bayesian lifetime models  censoring and truncation  classes of lifetime distributions  competing risk models  counting processes for lifetime data  degradation processes  goodness-of-fit  maintenance policies and replacement models  measurement errors  meta-analysis of lifetime data  models for multiple events  models for noncompliance  multivariate failure models  multi-state models  nonparametric estimation of survival functions  parametric estimation and predictive inference  parametric regression models  proportional hazard models and extensions  quality-of-life models  rank tests for comparing lifetime distributions  reliability methods  residual analysis and model diagnostics  surrogate marker processes and joint modeling of these processes with lifetime data. Officially cited as: Lifetime Data Anal.