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Lifetime Data Analysis

Lifetime Data Analysis

An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data

Editor-in-Chief: Mei-Ling T. Lee

ISSN: 1380-7870 (print version)
ISSN: 1572-9249 (electronic version)

Journal no. 10985

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Mei-Ling Ting Lee                                                                                
Department of Epidemiology and Biostatistics, University of Maryland, USA

Odd O. Aalen
Section of Medical Statistics, University of Oslo, Norway
Per Kragh Andersen
Department of Biostatistics, University of Copenhagen, Denmark
David Oakes
Department of Biostatistics and Computational Biology, University of Rochester, USA

Associate Editors:
Jianwen Cai, University of North Carolina, USA
Tianxi Cai, Harvard School of Public Health, USA
Chrys Caroni, National Technical University of Athens, Greece
I-Shou Chang, National Health Research Institutes, Taiwan
Ming-Hui Chen, University of Connecticut, USA
Ming-Yen Cheng, National Taiwan University, Taiwan
Ying Qing Chen, Fred Hutchinson Cancer Research Center, USA
Bernard F. Cole, University of Vermont, USA
Daniel Commenges, Université de Bordeaux II, France
Adam Ding, Northeastern University, USA
Thierry Duchesne, Université Laval, Canada
Jason Fine, University of North Carolina, USA
Mitchell H. Gail, National Cancer Institute, USA
Dave Glidden, University of California, USA
Steven Haberman, City University, UK
David Harrington, Dana-Farber Cancer Institute, USA
Xin He, University of Maryland, USA
Philip Hougaard, Lundbeck, Denmark
Chiung-Yu Huang, University of California at San Francisco, USA
Catherine Huber-Carol, Université René Descartes, France
Jong H. Jeong, University of Pittsburgh, USA
Zhezhen Jin, Columbia University, USA
Jack Kalbfleisch, University of Michigan, USA
Niels Keiding, University of Copenhagen, Denmark
Jialiang Li, National University of Singapore, Singapore
Yi Li, University of Michigan, USA
Bo Henry Lindqvist, Norwegian University of Science and Technology, Norway
Amita Manatunga, Emory University, USA
William Q. Meeker, Iowa State University, USA
Hideki Nagatsuka, Chuo University, Japan
Bin Nan, University of Michigan, USA
Hajime Uno, Dana-Farber Cancer Institute, USA
Michael Pennell, The Ohio State University, USA
Ruth Pfeiffer, National Cancer Institute, USA
Sven Ove Samuelsson, University of Oslo, Norway
Glen Satten, Center for Disease Control, USA
Douglas E. Schaubel, University of Michigan, USA
Thomas Scheike, University of Copenhagen, Denmark
Yu Shen, UT M.D. Anderson Cancer Center, USA
Jianguo Sun, University of Missouri, USA
Filia Vonta, National Technical University of Athens, Greece
Mei-Cheng Wang, Johns Hopkins University, USA
Xiao Wang, Purdue University, USA
G. Alex Whitmore, McGill University, Canada
Ronghui Lily Xu, University of California, USA
Song Yang, National Heart, Lung, and Blood Institute, USA
Mei-Jie Zhang, Medical College of Wisconsin, USA
Hongwei Zhao, Texas A&M Health Science Center, USA

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For authors and editors

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    2018 Impact Factor
  • 0.948
  • Aims and Scope

    Aims and Scope


    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

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