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Erschienen in: Lifetime Data Analysis 1/2018

20.12.2017 | Editorial

Special issue dedicated to Jack Kalbfleisch

verfasst von: Douglas E. Schaubel, Bin Nan

Erschienen in: Lifetime Data Analysis | Ausgabe 1/2018

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Excerpt

We are proud to present this special issue dedicated to Jack Kalbfleisch, Professor Emeritus of Biostatistics at the University of Michigan. Jack has made many landmark contributions to several areas of statistics, including mixed models, likelihood inference, nonparametric statistics, biased sampling, and multi-state models. He is best known for his work in survival analysis. For example, Kalbfleisch and Prentice (2002) is on the bookshelf of practically everyone researching or teaching survival analysis (> 15,000 citations). …

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Literatur
Zurück zum Zitat Choi J, Zeng D, Olshan AF, Cai J (2018) Joint modeling of survival time and longitudinal outcomes with flexible random effects. Lifetime Data Anal 24:126–152 Choi J, Zeng D, Olshan AF, Cai J (2018) Joint modeling of survival time and longitudinal outcomes with flexible random effects. Lifetime Data Anal 24:126–152
Zurück zum Zitat Hong HG, Kang J, Li Y (2018) Conditional screening for ultra-high dimensional covariates with survival outcomes. Lifetime Data Anal 24:45–71 Hong HG, Kang J, Li Y (2018) Conditional screening for ultra-high dimensional covariates with survival outcomes. Lifetime Data Anal 24:45–71
Zurück zum Zitat Kalbfleisch JD, Prentice RL (2002) The statistical analysis of failure time data. Wiley, New YorkCrossRefMATH Kalbfleisch JD, Prentice RL (2002) The statistical analysis of failure time data. Wiley, New YorkCrossRefMATH
Zurück zum Zitat Lawless JF (2018) Two-phase outcome-dependent studies for failure times and testing for effects of expensive covariates. Lifetime Data Anal 24:28–44 Lawless JF (2018) Two-phase outcome-dependent studies for failure times and testing for effects of expensive covariates. Lifetime Data Anal 24:28–44
Zurück zum Zitat Prentice RL, Zhao S (2018) Nonparametric estimation of the multivariate survivor function: the multivariate Kaplan-Meier estimator. Lifetime Data Anal 24:3–27 Prentice RL, Zhao S (2018) Nonparametric estimation of the multivariate survivor function: the multivariate Kaplan-Meier estimator. Lifetime Data Anal 24:3–27
Zurück zum Zitat Shinohara RT, Sun Y, Wang M-C (2018) Alternating event processes during lifetimes: population dynamics and statistical inference. Lifetime Data Anal 24:110–125 Shinohara RT, Sun Y, Wang M-C (2018) Alternating event processes during lifetimes: population dynamics and statistical inference. Lifetime Data Anal 24:110–125
Zurück zum Zitat Sildnes B, Lindqvist BH (2018) Modeling of semi-competing risks by means of first passage times of a stochastic process. Lifetime Data Anal 24:153–175 Sildnes B, Lindqvist BH (2018) Modeling of semi-competing risks by means of first passage times of a stochastic process. Lifetime Data Anal 24:153–175
Zurück zum Zitat Sun J, Xu D, Zhao H (2018) Joint analysis of interval-censored failure time data and panel count data. Lifetime Data Anal 24:94–109 Sun J, Xu D, Zhao H (2018) Joint analysis of interval-censored failure time data and panel count data. Lifetime Data Anal 24:94–109
Zurück zum Zitat Wang X, Schaubel DE (2018) Generalized estimating equations for restricted mean survival time under general censoring mechanisms. Lifetime Data Anal 24:176–199 Wang X, Schaubel DE (2018) Generalized estimating equations for restricted mean survival time under general censoring mechanisms. Lifetime Data Anal 24:176–199
Zurück zum Zitat Wu Y, Cook RJ (2018) Variable selection and prediction in biased samples with censored outcomes. Lifetime Data Anal 24:72–93 Wu Y, Cook RJ (2018) Variable selection and prediction in biased samples with censored outcomes. Lifetime Data Anal 24:72–93
Metadaten
Titel
Special issue dedicated to Jack Kalbfleisch
verfasst von
Douglas E. Schaubel
Bin Nan
Publikationsdatum
20.12.2017
Verlag
Springer US
Erschienen in
Lifetime Data Analysis / Ausgabe 1/2018
Print ISSN: 1380-7870
Elektronische ISSN: 1572-9249
DOI
https://doi.org/10.1007/s10985-017-9416-1

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