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