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.
寿命数据分析的目标是推进和促进处理寿命数据的各种应用领域的统计科学，包括：精算科学-经济学-工程科学-环境科学-管理科学-医学-运筹学-公共卫生-社会和行为科学。
The wild bootstrap for multivariate Nelson–Aalen estimators
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-018-9423-x
Vertical modeling: analysis of competing risks data with a cure fraction
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-018-9417-8
Improved precision in the analysis of randomized trials with survival outcomes, without assuming proportional hazards
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-018-9428-5
Modeling marginal features in studies of recurrent events in the presence of a terminal event
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-019-09462-4
Copula-based score test for bivariate time-to-event data, with application to a genetic study of AMD progression
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-018-09459-5
A class of semiparametric cure models with current status data
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-018-9420-0
Dealing with death when studying disease or physiological marker: the stochastic system approach to causality
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-018-9454-3
Reliability analysis of load-sharing systems with memory
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-018-9425-8
Additive hazards model with auxiliary subgroup survival information
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-018-9426-7
Goodness of fit tests for estimating equations based on pseudo-observations
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-018-9427-6
Semiparametric sieve maximum likelihood estimation under cure model with partly interval censored and left truncated data for application to spontaneous abortion
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-018-9445-4
New approaches for censored longitudinal data in joint modelling of longitudinal and survival data, with application to HIV vaccine studies
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-018-9434-7
Assessing the value of a censored surrogate outcome
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-019-09473-1
Landmark estimation of transition probabilities in non-Markov multi-state models with covariates
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-019-09474-0
The effect of omitted covariates in marginal and partially conditional recurrent event analyses
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-018-9430-y
Extending Bayesian back-calculation to estimate age and time specific HIV incidence
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-019-09465-1
The additive hazard estimator is consistent for continuous-time marginal structural models
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-019-09468-y
Group-sequential logrank methods for trial designs using bivariate non-competing event-time outcomes
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-019-09470-4
Model diagnostics for the proportional hazards model with length-biased data
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-018-9422-y
Prognostic score matching methods for estimating the average effect of a non-reversible binary time-dependent treatment on the survival function
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-019-09485-x
A semiparametric additive rates model for the weighted composite endpoint of recurrent and terminal events
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-019-09486-w
Partially hidden multi-state modelling of a prolonged disease state defined by a composite outcome
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-018-09460-y
Penalized full likelihood approach to variable selection for Cox’s regression model under nested case–control sampling
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-019-09475-z
Bayes factors for choosing among six common survival models
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-018-9429-4
Multiple event times in the presence of informative censoring: modeling and analysis by copulas
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-019-09490-0
Multiplicative rates model for recurrent events in case-cohort studies
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-019-09466-0
Correction to: Improved precision in the analysis of randomized trials with survival outcomes, without assuming proportional hazards
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-019-09484-y
Semiparametric regression analysis of doubly censored failure time data from cohort studies
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-019-09477-x
Robust estimation in accelerated failure time models
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-018-9421-z
An extended proportional hazards model for interval-censored data subject to instantaneous failures
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-019-09467-z
The Wally plot approach to assess the calibration of clinical prediction models
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-017-9414-3
Parametric modelling of prevalent cohort data with uncertainty in the measurement of the initial onset date
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-019-09481-1
Semiparametric temporal process regression of survival-out-of-hospital
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-018-9433-8
Semiparametric inference for a two-stage outcome-dependent sampling design with interval-censored failure time data
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-019-09461-5
Prevalent cohort studies and unobserved heterogeneity.
来源期刊：Lifetime data analysisDOI：10.1007/s10985-019-09479-9
Varying coefficient transformation cure models for failure time data
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-019-09488-8
Tree-based modeling of time-varying coefficients in discrete time-to-event models
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-019-09489-7
Bootstrap and permutation rank tests for proportional hazards under right censoring
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-019-09487-9
A new long-term survival model with dispersion induced by discrete frailty
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-019-09472-2
Mixture regression models for the gap time distributions and illness–death processes
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-018-9418-7
A dual frailty model for lifetime analysis in maritime transportation
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-019-09463-3
A causal proportional hazards estimator under homogeneous or heterogeneous selection in an IV setting
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-019-09476-y
Semiparametric methods for survival data with measurement error under additive hazards cure rate models
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-019-09482-0
Hidden three-state survival model for bivariate longitudinal count data
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-018-9448-1
Weighted estimation for multivariate shared frailty models for complex surveys
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-019-09469-x
Testing for center effects on survival and competing risks outcomes using pseudo-value regression
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-018-9443-6
Proportional cross-ratio model
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-018-9451-6
Parametric estimation of association in bivariate failure-time data subject to competing risks: sensitivity to underlying assumptions
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-018-9438-3
A Bayesian approach for semiparametric regression analysis of panel count data
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-019-09471-3
Group sequential tests for treatment effect on survival and cumulative incidence at a fixed time point
来源期刊：Lifetime Data AnalysisDOI：10.1007/s10985-019-09491-z
