IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v66y2010i2p327-335.html
   My bibliography  Save this article

Joint Inference on HIV Viral Dynamics and Immune Suppression in Presence of Measurement Errors

Author

Listed:
  • L. Wu
  • W. Liu
  • X. J. Hu

Abstract

No abstract is available for this item.

Suggested Citation

  • L. Wu & W. Liu & X. J. Hu, 2010. "Joint Inference on HIV Viral Dynamics and Immune Suppression in Presence of Measurement Errors," Biometrics, The International Biometric Society, vol. 66(2), pages 327-335, June.
    • Handle: RePEc:bla:biomet:v:66:y:2010:i:2:p:327-335
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2009.01308.x
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Joseph G. Ibrahim & Ming-Hui Chen & Stuart R. Lipsitz & Amy H. Herring, 2005. "Missing-Data Methods for Generalized Linear Models: A Comparative Review," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 332-346, March.
    2. Philip Hougaard, 1999. "Fundamentals of Survival Data," Biometrics, The International Biometric Society, vol. 55(1), pages 13-22, March.
    3. Joe, Harry, 2008. "Accuracy of Laplace approximation for discrete response mixed models," Computational Statistics & Data Analysis, Elsevier, vol. 52(12), pages 5066-5074, August.
    4. John A. Rice & Colin O. Wu, 2001. "Nonparametric Mixed Effects Models for Unequally Sampled Noisy Curves," Biometrics, The International Biometric Society, vol. 57(1), pages 253-259, March.
    5. Yi-Kuan Tseng & Fushing Hsieh & Jane-Ling Wang, 2005. "Joint modelling of accelerated failure time and longitudinal data," Biometrika, Biometrika Trust, vol. 92(3), pages 587-603, September.
    6. Wei Liu & Lang Wu, 2007. "Simultaneous Inference for Semiparametric Nonlinear Mixed-Effects Models with Covariate Measurement Errors and Missing Responses," Biometrics, The International Biometric Society, vol. 63(2), pages 342-350, June.
    7. Hulin Wu & A. Adam Ding, 1999. "Population HIV-1 Dynamics In Vivo: Applicable Models and Inferential Tools for Virological Data from AIDS Clinical Trials," Biometrics, The International Biometric Society, vol. 55(2), pages 410-418, June.
    8. Wu L., 2002. "A Joint Model for Nonlinear Mixed-Effects Models With Censoring and Covariates Measured With Error, With Application to AIDS Studies," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 955-964, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hanze Zhang & Yangxin Huang, 2020. "Quantile regression-based Bayesian joint modeling analysis of longitudinal–survival data, with application to an AIDS cohort study," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(2), pages 339-368, April.
    2. Melkamu Molla Ferede & Samuel Mwalili & Getachew Dagne & Simon Karanja & Workagegnehu Hailu & Mahmoud El-Morshedy & Afrah Al-Bossly, 2022. "A Semiparametric Bayesian Joint Modelling of Skewed Longitudinal and Competing Risks Failure Time Data: With Application to Chronic Kidney Disease," Mathematics, MDPI, vol. 10(24), pages 1-21, December.
    3. 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.
    4. Matos, Larissa A. & Bandyopadhyay, Dipankar & Castro, Luis M. & Lachos, Victor H., 2015. "Influence assessment in censored mixed-effects models using the multivariate Student’s-t distribution," Journal of Multivariate Analysis, Elsevier, vol. 141(C), pages 104-117.
    5. Yih‐Huei Huang & Wen‐Han Hwang & Fei‐Yin Chen, 2016. "Improving efficiency using the Rao–Blackwell theorem in corrected and conditional score estimation methods for joint models," Biometrics, The International Biometric Society, vol. 72(4), pages 1136-1144, December.
    6. Shahedul A. Khan & Nyla Basharat, 2022. "Accelerated failure time models for recurrent event data analysis and joint modeling," Computational Statistics, Springer, vol. 37(4), pages 1569-1597, September.
    7. Trevor J. Thomson & X. Joan Hu & Bohdan Nosyk, 2024. "Evaluating Effects of Various Exposures on Mortality Risk of Opioid Use Disorders with Linked Administrative Databases," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 16(2), pages 416-434, July.
    8. 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.
    9. Lisa M. McCrink & Adele H. Marshall & Karen J. Cairns, 2013. "Advances in Joint Modelling: A Review of Recent Developments with Application to the Survival of End Stage Renal Disease Patients," International Statistical Review, International Statistical Institute, vol. 81(2), pages 249-269, August.
    10. Yangxin Huang & X. Hu & Getachew Dagne, 2014. "Jointly modeling time-to-event and longitudinal data: a Bayesian approach," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(1), pages 95-121, March.
    11. Hongbin Zhang & Lang Wu, 2018. "A non‐linear model for censored and mismeasured time varying covariates in survival models, with applications in human immunodeficiency virus and acquired immune deficiency syndrome studies," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(5), pages 1437-1450, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lu, Xiaosun & Huang, Yangxin & Zhu, Yiliang, 2016. "Finite mixture of nonlinear mixed-effects joint models in the presence of missing and mismeasured covariate, with application to AIDS studies," Computational Statistics & Data Analysis, Elsevier, vol. 93(C), pages 119-130.
    2. Hongbin Zhang & Lang Wu, 2018. "A non‐linear model for censored and mismeasured time varying covariates in survival models, with applications in human immunodeficiency virus and acquired immune deficiency syndrome studies," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(5), pages 1437-1450, November.
    3. Dagne Getachew & Huang Yangxin, 2012. "Bayesian inference for a nonlinear mixed-effects Tobit model with multivariate skew-t distributions: application to AIDS studies," The International Journal of Biostatistics, De Gruyter, vol. 8(1), pages 1-24, September.
    4. Yangxin Huang & Getachew Dagne, 2011. "A Bayesian Approach to Joint Mixed-Effects Models with a Skew-Normal Distribution and Measurement Errors in Covariates," Biometrics, The International Biometric Society, vol. 67(1), pages 260-269, March.
    5. Hanze Zhang & Yangxin Huang, 2020. "Quantile regression-based Bayesian joint modeling analysis of longitudinal–survival data, with application to an AIDS cohort study," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(2), pages 339-368, April.
    6. Liu, Wei & Wu, Lang, 2008. "A semiparametric nonlinear mixed-effects model with non-ignorable missing data and measurement errors for HIV viral data," Computational Statistics & Data Analysis, Elsevier, vol. 53(1), pages 112-122, September.
    7. Yangxin Huang & X. Hu & Getachew Dagne, 2014. "Jointly modeling time-to-event and longitudinal data: a Bayesian approach," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(1), pages 95-121, March.
    8. Wei Liu & Lang Wu, 2012. "Two-step and likelihood methods for HIV viral dynamic models with covariate measurement errors and missing data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(5), pages 963-978, October.
    9. Wei Liu & Lang Wu, 2007. "Simultaneous Inference for Semiparametric Nonlinear Mixed-Effects Models with Covariate Measurement Errors and Missing Responses," Biometrics, The International Biometric Society, vol. 63(2), pages 342-350, June.
    10. Wei Liu & Shuyou Li, 2015. "A multiple imputation approach to nonlinear mixed-effects models with covariate measurement errors and missing values," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(3), pages 463-476, March.
    11. Jianwei Chen, 2010. "Modelling long‐term human immunodeficiency virus dynamic models with application to acquired immune deficiency syndrome clinical study," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 59(5), pages 805-820, November.
    12. Noh, Maengseok & Wu, Lang & Lee, Youngjo, 2012. "Hierarchical likelihood methods for nonlinear and generalized linear mixed models with missing data and measurement errors in covariates," Journal of Multivariate Analysis, Elsevier, vol. 109(C), pages 42-51.
    13. Hua Liang, 2009. "Generalized partially linear mixed-effects models incorporating mismeasured covariates," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 61(1), pages 27-46, March.
    14. Vaida, Florin & Fitzgerald, Anthony P. & DeGruttola, Victor, 2007. "Efficient hybrid EM for linear and nonlinear mixed effects models with censored response," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 5718-5730, August.
    15. Larissa A. Matos & Luis M. Castro & Víctor H. Lachos, 2016. "Censored mixed-effects models for irregularly observed repeated measures with applications to HIV viral loads," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(4), pages 627-653, December.
    16. Jimin Ding & Jane-Ling Wang, 2008. "Modeling Longitudinal Data with Nonparametric Multiplicative Random Effects Jointly with Survival Data," Biometrics, The International Biometric Society, vol. 64(2), pages 546-556, June.
    17. Hyejin KO & Marie Davidian, 2000. "Correcting for Measurement Error in Individual-Level Covariates in Nonlinear Mixed Effects Models," Biometrics, The International Biometric Society, vol. 56(2), pages 368-375, June.
    18. Jaroslaw Harezlak & Louise M. Ryan & Jay N. Giedd & Nicholas Lange, 2005. "Individual and Population Penalized Regression Splines for Accelerated Longitudinal Designs," Biometrics, The International Biometric Society, vol. 61(4), pages 1037-1048, December.
    19. Ye, Mao & Lu, Zhao-Hua & Li, Yimei & Song, Xinyuan, 2019. "Finite mixture of varying coefficient model: Estimation and component selection," Journal of Multivariate Analysis, Elsevier, vol. 171(C), pages 452-474.
    20. Getachew A. Dagne, 2016. "A growth mixture Tobit model: application to AIDS studies," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(7), pages 1174-1185, July.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:biomet:v:66:y:2010:i:2:p:327-335. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0006-341X .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.