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Regression Analysis When Covariates Are Regression Parameters of a Random Effects Model for Observed Longitudinal Measurements

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  • C. Y. Wang
  • Naisyin Wang
  • Suojin Wang

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  • C. Y. Wang & Naisyin Wang & Suojin Wang, 2000. "Regression Analysis When Covariates Are Regression Parameters of a Random Effects Model for Observed Longitudinal Measurements," Biometrics, The International Biometric Society, vol. 56(2), pages 487-495, June.
    • Handle: RePEc:bla:biomet:v:56:y:2000:i:2:p:487-495
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    File URL: http://hdl.handle.net/10.1111/j.0006-341X.2000.00487.x
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    References listed on IDEAS

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    1. Wang, C. Y., 1999. "Robust sandwich covariance estimation for regression calibration estimator in Cox regression with measurement error," Statistics & Probability Letters, Elsevier, vol. 45(4), pages 371-378, December.
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    1. Siti Haslinda Mohd Din & Marek Molas & Jolanda Luime & Emmanuel Lesaffre, 2014. "Longitudinal profiles of bounded outcome scores as predictors for disease activity in rheumatoid arthritis patients: a joint modeling approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(8), pages 1627-1644, August.
    2. Erning Li & Naisyin Wang & Nae-Yuh Wang, 2007. "Joint Models for a Primary Endpoint and Multiple Longitudinal Covariate Processes," Biometrics, The International Biometric Society, vol. 63(4), pages 1068-1078, December.
    3. Li, Erning & Zhang, Daowen & Davidian, Marie, 2007. "Likelihood and pseudo-likelihood methods for semiparametric joint models for a primary endpoint and longitudinal data," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 5776-5790, August.
    4. Xianzheng Huang & Leonard A. Stefanski & Marie Davidian, 2009. "Latent-Model Robustness in Joint Models for a Primary Endpoint and a Longitudinal Process," Biometrics, The International Biometric Society, vol. 65(3), pages 719-727, September.
    5. Ching‐Yun Wang & Xiao Song, 2021. "Semiparametric regression calibration for general hazard models in survival analysis with covariate measurement error; surprising performance under linear hazard," Biometrics, The International Biometric Society, vol. 77(2), pages 561-572, June.
    6. Xiao Song & C. Y. Wang, 2008. "Semiparametric Approaches for Joint Modeling of Longitudinal and Survival Data with Time-Varying Coefficients," Biometrics, The International Biometric Society, vol. 64(2), pages 557-566, June.
    7. Bernhardt, Paul W. & Zhang, Daowen & Wang, Huixia Judy, 2015. "A fast EM algorithm for fitting joint models of a binary response and multiple longitudinal covariates subject to detection limits," Computational Statistics & Data Analysis, Elsevier, vol. 85(C), pages 37-53.
    8. Yi, Fengting & Tang, Niansheng & Sun, Jianguo, 2020. "Regression analysis of interval-censored failure time data with time-dependent covariates," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
    9. Duchwan Ryu & Erning Li & Bani K. Mallick, 2011. "Bayesian Nonparametric Regression Analysis of Data with Random Effects Covariates from Longitudinal Measurements," Biometrics, The International Biometric Society, vol. 67(2), pages 454-466, June.
    10. Jaeun Choi & Donglin Zeng & Andrew F. Olshan & Jianwen Cai, 2018. "Joint modeling of survival time and longitudinal outcomes with flexible random effects," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 24(1), pages 126-152, January.
    11. Samuel Iddi & Geert Molenberghs, 2012. "A joint marginalized multilevel model for longitudinal outcomes," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(11), pages 2413-2430, July.
    12. Ching-Yun Wang & Jean de Dieu Tapsoba & Catherine Duggan & Anne McTiernan, 2024. "Generalized Linear Models with Covariate Measurement Error and Zero-Inflated Surrogates," Mathematics, MDPI, vol. 12(2), pages 1-14, January.
    13. Stoklosa, Jakub & Dann, Peter & Huggins, Richard M. & Hwang, Wen-Han, 2016. "Estimation of survival and capture probabilities in open population capture–recapture models when covariates are subject to measurement error," Computational Statistics & Data Analysis, Elsevier, vol. 96(C), pages 74-86.
    14. Yun Fang & Li-Xing Zhu, 2012. "Asymptotics of SIMEX-based variance estimation," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 75(3), pages 329-345, April.
    15. De la Cruz, Rolando & Meza, Cristian & Arribas-Gil, Ana & Carroll, Raymond J., 2016. "Bayesian regression analysis of data with random effects covariates from nonlinear longitudinal measurements," Journal of Multivariate Analysis, Elsevier, vol. 143(C), pages 94-106.
    16. Brent A Coull, 2011. "A Random Intercepts–Functional Slopes Model for Flexible Assessment of Susceptibility in Longitudinal Designs," Biometrics, The International Biometric Society, vol. 67(2), pages 486-494, June.
    17. E. Andrés Houseman & Carmen Marsit & Margaret Karagas & Louise M. Ryan, 2007. "Penalized Item Response Theory Models: Application to Epigenetic Alterations in Bladder Cancer," Biometrics, The International Biometric Society, vol. 63(4), pages 1269-1277, December.
    18. Wang, C. Y. & Huang, Yijian, 2001. "Functional methods for logistic regression on random-effect-coefficients for longitudinal measurements," Statistics & Probability Letters, Elsevier, vol. 53(4), pages 347-356, July.

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