Statistical inference for the accelerated failure time model under two-stage generalized case–cohort design

References

• Andersen, P. K., and R. D. Gill. 1982. Cox’s regression model for counting processes: a large sample study. The Annals of Statistics 10 (4):1100–20.
   Web of Science ®Google Scholar
• Breslow, N. E., and K. C. Cain. 1988. Logistic regression for two-stage case-control data. Biometrika 75 (1):11–20.
   Web of Science ®Google Scholar
• Brown, B. M., and Y. G. Wang. 2007. Induced smoothing for rank regression with censored survival times. Statistics in Medicine 26 (4):828–36.
   PubMed Web of Science ®Google Scholar
• Cao, Y., Q. Yang, and J. Yu. 2017. Optimal generalized case-cohort analysis with accelerated failure time model. Journal of the Korean Statistical Society 46 (2):298–307.
   Web of Science ®Google Scholar
• Chatterjee, N., Y. Chen, and N. Breslow. 2003. A pseudo-score estimator for regression problems with two-phase sampling. Journal of the American Statistical Association 98 (461):158–68.
   Web of Science ®Google Scholar
• Chen, K. 2001. Generalized case–cohort sampling. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 63 (4):791–809.
   Google Scholar
• Chen, K., and S. H. Lo. 1999. Case–cohort and case–control analysis with cox’s model. Biometrika 86 (4):755–64.
   Web of Science ®Google Scholar
• Eubank, R. L. 1988. Smoothing spline and nonparametric regression. New York: Dekker.
   Google Scholar
• Green, D. M., N. E. Breslow, J. B. Beckwith, J. Z. Finklestein, P. E. Grundy, P. R. Thomas, T. Kim, S. J. Shochat, G. M. Haase, M. L. Ritchey, et al. 1998. Comparison between single-dose and divided-dose administration of dactinomycin and doxorubicin for patients with Wilms’ tumor: A report from the national Wilms’ tumor study. Journal of Clinical Oncology 16 (1):237–45.
   PubMed Web of Science ®Google Scholar
• Johnson, L., and R. Strawderman. 2009. Induced smoothing for the semiparametric accelerated failure time model: asymptotics and extensions to clustered data. Biometrika 96 (3):577–90.
   PubMed Web of Science ®Google Scholar
• Kang, S., and J. Cai. 2009. Marginal hazards model for case-cohort studies with multiple disease outcomes. Biometrika 96 (4):887–901.
   PubMed Web of Science ®Google Scholar
• Kang, S., J. Cai, and L. Chambless. 2013. Marginal additive hazards model for case–cohort studies with multiple disease outcomes: An application to the atherosclerosis risk in communities (ARIC) study. Biostatistics 14 (1):28–41.
   PubMed Web of Science ®Google Scholar
• Kim, S., J. Cai, and W. Lu. 2013. More efficient estimators for case-cohort studies. Biometrika 100 (3):695–708.
   PubMed Web of Science ®Google Scholar
• Kong, L., and J. Cai, 2009. Case-cohort analysis with accelerated failure time model. Biometrics 65 (1):135–42.
   PubMed Web of Science ®Google Scholar
• Kong, L., J. Cai, and P. K. Sen. 2004. Weighted estimating equations for semiparametric transformation models with censored data from a case–cohort design. Biometrika 91 (2):305–19.
   Web of Science ®Google Scholar
• Kosorok, M. R. 2008. Introduction to empirical processes and semiparametric inference. New York: Springer.
   Google Scholar
• Kulich, M., and D. Y. Lin. 2000. Additive hazards regression with covariate measurement error. Journal of the American Statistical Association 95 (449):238–48.
   Web of Science ®Google Scholar
• Lin, D. Y., L. J. Wei, I. Yang, and Z. Ying. 2000. Semiparametric regression for the mean and rate functions of recurrent events. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 62 (4):711–30.
   Google Scholar
• Liu, Y. Y., H. B. Zhou, and J. Cai. 2009. Estimated pseudopartial-likelihood method for correlated failure time data with auxiliary covariates. Biometrics 65 (4):1184–93.
   PubMed Web of Science ®Google Scholar
• Liu, Y. Y., Y. S. Wu, and H. Zhou. 2010. Multivariate failure times regression with a continuous auxiliary covariate. Journal of Multivariate Analysis 101 (3):679–91.
   PubMed Web of Science ®Google Scholar
• Lu, W. B., and A. A. Tsiatis. 2006. Semiparametric transformation models for the case–cohort study. Biometrika 93 (1):207–14.
   Web of Science ®Google Scholar
• Nan, B., M. Yu, and J. D. Kalbfleisch. 2006. Censored linear regression for case–cohort studies. Biometrika 93 (4):747–62.
   Web of Science ®Google Scholar
• Neyman, J. 1938. Contribution to the theory of sampling from human populations. Journal of the American Statistical Association 33 (201):101–16.
   Google Scholar
• Pollard, D. 1990. Empirical processes: Theory and applications. Hayward: Institute of Mathematical Statistics.
   Google Scholar
• Prentice, R. L. 1986. A case–cohort design for epidemiologic cohort studies and disease prevention trials. Biometrika 73 (1):1–11.
   Web of Science ®Google Scholar
• Self, S. G., and R. L. Prentice. 1988. Asymptotic distribution theory and efficiency results for case–cohort studies. The Annals of Statistics 16 (1):64–81.
   Web of Science ®Google Scholar
• Shi, X. P., Y. Y. Liu, and Y. S. Wu. 2014. Continuous auxiliary covariate in additive hazards regression for survival data. Journal of Systems Science and Complexity 27 (6):1247–62.
   Web of Science ®Google Scholar
• Sun, Y., X. Qian, Q. Shou, and P. Gilbert. 2017. Analysis of two-phase sampling data with semiparametric additive hazards models. Lifetime Data Analysis 23 (3):377–99.
   PubMed Web of Science ®Google Scholar
• Yin, G., H. Li, and D. Zeng. 2008. Partially linear additive hazards regression with varying coefficients. Journal of the American Statistical Association 103 (483):1200–13.
   Web of Science ®Google Scholar
• Ying, Z. 1993. A large sample study of rank estimation for censored regression data. The Annals of Statistics 21 (1):76–99.
   Web of Science ®Google Scholar
• Yu, J., Y. Liu, D. P. Sandler, and H. Zhou. 2015. Statistical inference for the additive hazards model under outcome-dependent sampling. Canadian Journal of Statistics 43 (3):436–53.
   PubMed Web of Science ®Google Scholar
• Yu, J., Y. Liu, J. Cai, D. P. Sandler, and H. Zhou. 2016. Outcome-dependent sampling design and inference for cox’s proportional hazards model. Journal of Statistical Planning and Inference 178 :24–36.
   PubMed Web of Science ®Google Scholar
• Zeng, D., and D. Y. Lin. 2014. Efficient estimation of semiparametric transformation models for two-phase cohort studies. Journal of the American Statistical Association 109 (505):371–83.
   PubMed Web of Science ®Google Scholar
• Zhou, H., W. Xu, D. Zeng, and J. Cai. 2014. Semiparametric inference for data with a continuous outcome from a two-phase probability-dependent sampling scheme. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 76 (1):197–215.
   PubMed Web of Science ®Google Scholar