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Original Articles

Estimation of marginal generalized linear model with subgroup auxiliary information

, , &
Pages 837-855 | Received 20 Jun 2018, Accepted 03 Jul 2019, Published online: 22 Jul 2019

References

  • Chatterjee, N., Y. H. Chen, P. Maas, and R. Carroll. 2016. Constrained maximum likelihood estimation for model calibration using summary-level information from external big data sources. Journal of American Statistical Association 111 (513):107–17. doi:10.1080/01621459.2015.1123157.
  • Hansen, L. P. 1982. Large sample properties of generalized method of moments estimators. Econometrica 50 (4):1029–54. doi:10.2307/1912775.
  • He, J., H. Li, S. M. Zhang, and X. G. Duan. 2019. Additive hazards model with auxiliary subgroup survival information. Lifetime Data Analysis 25 (1):128–49. doi:10.1007/s10985-018-9426-7.
  • Huang, C. Y., J. Qin, and H. T. Tsai. 2016. Efficient estimation of the Cox model with auxiliary subgroup survival information. Journal of American Statistical Association 111 (514):787–99. doi:10.1080/01621459.2015.1044090.
  • Lee, Y., and J. A. Nelder. 2004. Conditional and marginal models: Another view. Statistical Science 19 (2):219–38. doi:10.1214/088342304000000305.
  • Li, H., X. G. Duan, and G. S. Yin. 2016. Generalized method of moments for additive hazards model with clustered dental survival data. Scandinavian Journal of Statistics 43 (4):1124–39. doi:10.1111/sjos.12232.
  • Li, H., and G. S. Yin. 2009. Generalized method of moments estimation for linear regression with clustered failure time data. Biometrika 96 (2):293–306. doi:10.1093/biomet/asp005.
  • Liang, K. Y., and S. L. Zeger. 1986. Longitudinal data analysis using generalized linear models. Biometrika 73 (1):13–22. doi:10.1093/biomet/73.1.13.
  • Lin, D., and Z. Ying. 1994. Semiparametric analysis of the additive risk model. Biometrika 81 (1):61–71. doi:10.2307/2337050.
  • McCullagh, P., and J. A. Nelder. 1989. Generalized linear models. New York, NY: Chapman and Hall.
  • Nelder, J. A., and R. W. M. Wedderburn. 1972. Generalized linear models. Journal of the Royal Statistical Society. Series A 135 (3):370–84. doi:10.2307/2344614.
  • Qin, J., H. Zhang, P. F. Li, D. Albanes, and K. Yu. 2015. Using covariate-specific disease prevalence information to increase the power of case-control studies. Biometrika 102 (1):169–80. doi:10.1093/biomet/asu048.
  • Qu, A., B. G. Lindsay, and B. Li. 2000. Improving generalised estimating equations using quadratic inference functions. Biometrika 87 (4):823–36. doi:10.1093/biomet/87.4.823.
  • Qu, A., and R. Z. Li. 2006. Quadratic inference functions for varying-coefficient models with longitudinal data. Biometrics 62 (2):379–91. doi:10.1111/j.1541-0420.2005.00490.x.
  • Song, P. X.-K. 2007. Correlated data analysis: Modeling, analytics, and applications. New York, NY: Springer Science & Business Media.

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