Access the full text.
Sign up today, get DeepDyve free for 14 days.
Loading next page...
/lp/springer-journals/asymptotic-theory-for-relative-risk-models-with-missing-time-dependent-EyQlP2Ubf7
References (42)
-
H. Chen, R. Little (1999)
Proportional hazards regression with missing covariatesJournal of the American Statistical Association, 94
-
N. Breslow (1974)
Covariance analysis of censored survival data.Biometrics, 30 1
-
M. Paik, W. Tsai (1997)
On using the Cox proportional hazards model with missing covariatesBiometrika, 84
-
D. Kalbfleisch John, L. Ross (2002)
Prentice. The Statistical Analysis of Failure Time Data -
D. Lin, Z. Ying (1993)
Cox Regression with Incomplete Covariate MeasurementsJournal of the American Statistical Association, 88
-
L. George (2003)
The Statistical Analysis of Failure Time DataTechnometrics, 45
-
A. Dempster, N. Laird, D. Rubin (1977)
Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper -
J.F. Dupuy (2006)
Estimation in a change-point hazard regression modelJ. Roy. Statist. Soc. Ser. B., 39
-
A.P. Dempster, N.M. Laird, D.B. Rubin (1977)
Maximum likelihood from incomplete data via the EM algorithmBiometrika, 62
-
Javier Flores, J. Cavanaugh (2018)
Partial LikelihoodWiley StatsRef: Statistics Reference Online
-
Subir Ghosh, R. Little, D. Rubin (2020)
Missing DataDefinitions
-
P.K. Anderson, R.D. Gill (1982)
Cox’s regression model for counting processes: a large sample studyAnn. Statist., 10
-
J. Dupuy, Ion Grama, M. Mesbah (2006)
Asymptotic theory for the Cox model with missing time-dependent covariateAnnals of Statistics, 34
-
Mai Zhou (2001)
Understanding the Cox Regression Models With Time-Change CovariatesThe American Statistician, 55
-
P. Bickel (1993)
Efficient and Adaptive Estimation for Semiparametric Models -
R. Kosorok Michael (2008)
Introduction to Empirical Processes and Semiparametric Inference -
D. Lin, Z. Ying (1994)
Semiparametric analysis of the additive risk modelBiometrika, 81
-
O. Aalen (1980)
A Model for Nonparametric Regression Analysis of Counting Processes -
Ka-young Park, P. Qiu (2014)
Model selection and diagnostics for joint modeling of survival and longitudinal data with crossing hazard rate functionsStatistics in Medicine, 33
-
N. Breslow, J. Lubin, P. Marek, B. Langholz (1983)
Multiplicative Models and Cohort AnalysisJournal of the American Statistical Association, 78
-
Yu-Ru Su, Jane-ling Wang (2012)
MODELING LEFT-TRUNCATED AND RIGHT-CENSORED SURVIVAL DATA WITH LONGITUDINAL COVARIATES.Annals of statistics, 40 3
-
Haibo Zhou, M. Pepe (1995)
Auxiliary covariate data in failure time regressionBiometrika, 82
-
R. Kay (2012)
The Analysis of Survival Data -
S. Self, R. Prentice (1982)
Commentary on Andersen and Gill's "Cox's Regression Model for Counting Processes: A Large Sample Study"Annals of Statistics, 10
-
(1998)
Asymptotic Statistics -
E. Parner (1998)
Asymptotic theory for the correlated gamma-frailty modelAnnals of Statistics, 26
-
D. Byar, N. Mantel (1975)
Some interrelationships among the regression coefficient estimates arising in a class of models appropriate to response-time data.Biometrics, 31 4
-
T. Nummi (2009)
Introduction to Empirical Processes and Semiparametric Inference by Michael R. KosorokInternational Statistical Review, 77
-
J. Dupuy (2006)
Estimation in a change-point hazard regression modelStatistics & Probability Letters, 76
-
R. Little, D. Rubin (2019)
Statistical Analysis with Missing Data, Third EditionWiley Series in Probability and Statistics
-
(1981)
Abstract inference. Wiley Series in Probability and Mathematical Statistics -
Angélica Hernández-Quintero, J. Dupuy, Gabriel Escarela (2011)
Analysis of a semiparametric mixture model for competing risksAnnals of the Institute of Statistical Mathematics, 63
-
S. Murphy (1995)
Asymptotic Theory for the Frailty ModelAnnals of Statistics, 23
-
D., R., Cox
Regression Models and Life-Tables -
J.A. Little Roderick, B. Rubin Donald (2014)
Statistical Analysis with Missing Data -
Duncan Thomas (1981)
General relative-risk models for survival time and matched case-control analysisBiometrics, 37
-
M. Wulfsohn, A. Tsiatis (1997)
A joint model for survival and longitudinal data measured with error.Biometrics, 53 1
-
T. Mikosch, A. Vaart, J. Wellner (1996)
Weak Convergence and Empirical Processes: With Applications to Statistics -
S. Murphy (1994)
Consistency in a Proportional Hazards Model Incorporating a Random EffectAnnals of Statistics, 22
-
O.O. Aalen (1980)
Lecture Notes in Statistics -
D.Y. Lin, Z. Ying (1993)
Cox regression with incomplete covariate measurementsJ. Amer. Statistit. Assoc., 88
-
J. Dupuy (2005)
The proportional hazards model with covariate measurement errorJournal of Statistical Planning and Inference, 135
- Publisher
- Springer Journals
- Copyright
- Copyright © 2018 by Institute of Applied Mathematics, Academy of Mathematics and System Sciences, Chinese Academy of Sciences and Springer-Verlag GmbH Germany, part of Springer Nature
- Subject
- Mathematics; Applications of Mathematics; Math Applications in Computer Science; Theoretical, Mathematical and Computational Physics
- ISSN
- 0168-9673
- eISSN
- 1618-3932
- DOI
- 10.1007/s10255-018-0776-4
- Publisher site
- See Article on Publisher Site
Abstract
Relative-risk models are often used to characterize the relationship between survival time and time-dependent covariates. When the covariates are observed, the estimation and asymptotic theory for parameters of interest are available; challenges remain when missingness occurs. A popular approach at hand is to jointly model survival data and longitudinal data. This seems efficient, in making use of more information, but the rigorous theoretical studies have long been ignored. For both additive risk models and relative-risk models, we consider the missing data nonignorable. Under general regularity conditions, we prove asymptotic normality for the nonparametric maximum likelihood estimators.
Journal
Acta Mathematicae Applicatae Sinica – Springer Journals
Published: Oct 4, 2018