IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v58y2002i1p98-109.html
   My bibliography  Save this article

Frailty Models with Missing Covariates

Author

Listed:
  • Amy H. Herring
  • Joseph G. Ibrahim
  • Stuart R. Lipsitz

Abstract

No abstract is available for this item.

Suggested Citation

  • Amy H. Herring & Joseph G. Ibrahim & Stuart R. Lipsitz, 2002. "Frailty Models with Missing Covariates," Biometrics, The International Biometric Society, vol. 58(1), pages 98-109, March.
    • Handle: RePEc:bla:biomet:v:58:y:2002:i:1:p:98-109
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/j.0006-341X.2002.00098.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. J. G. Ibrahim & S. R. Lipsitz & M.‐H. Chen, 1999. "Missing covariates in generalized linear models when the missing data mechanism is non‐ignorable," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(1), pages 173-190.
    2. Els Goetghebeur & Louise Ryan, 2000. "Semiparametric Regression Analysis of Interval-Censored Data," Biometrics, The International Biometric Society, vol. 56(4), pages 1139-1144, December.
    3. W. R. Gilks & P. Wild, 1992. "Adaptive Rejection Sampling for Gibbs Sampling," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 41(2), pages 337-348, June.
    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. Chen, Ming-Hui & Ibrahim, Joseph G. & Shao, Qi-Man, 2009. "Maximum likelihood inference for the Cox regression model with applications to missing covariates," Journal of Multivariate Analysis, Elsevier, vol. 100(9), pages 2018-2030, October.
    2. Malay Naskar & Kalyan Das & Joseph G. Ibrahim, 2005. "A Semiparametric Mixture Model for Analyzing Clustered Competing Risks Data," Biometrics, The International Biometric Society, vol. 61(3), pages 729-737, September.
    3. Joseph Ibrahim & Geert Molenberghs, 2009. "Missing data methods in longitudinal studies: a review," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 18(1), pages 1-43, May.

    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. Kalyan Das & Angshuman Sarkar, 2014. "Robust inference for generalized partially linear mixed models that account for censored responses and missing covariates -- an application to Arctic data analysis," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(11), pages 2418-2436, November.
    2. Ming‐Hui Chen & Joseph G. Ibrahim, 2001. "Maximum Likelihood Methods for Cure Rate Models with Missing Covariates," Biometrics, The International Biometric Society, vol. 57(1), pages 43-52, March.
    3. Ruiwen Zhou & Huiqiong Li & Jianguo Sun & Niansheng Tang, 2022. "A new approach to estimation of the proportional hazards model based on interval-censored data with missing covariates," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 28(3), pages 335-355, July.
    4. Lee, Min Cherng & Mitra, Robin, 2016. "Multiply imputing missing values in data sets with mixed measurement scales using a sequence of generalised linear models," Computational Statistics & Data Analysis, Elsevier, vol. 95(C), pages 24-38.
    5. Shu Yang & Jae Kwang Kim, 2016. "Likelihood-based Inference with Missing Data Under Missing-at-Random," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(2), pages 436-454, June.
    6. Tamara Broderick & Robert Gramacy, 2011. "Classification and Categorical Inputs with Treed Gaussian Process Models," Journal of Classification, Springer;The Classification Society, vol. 28(2), pages 244-270, July.
    7. Pang, W. K. & Yang, Z. H. & Hou, S. H. & Leung, P. K., 2002. "Non-uniform random variate generation by the vertical strip method," European Journal of Operational Research, Elsevier, vol. 142(3), pages 595-609, November.
    8. Roy, Vivekananda, 2014. "Efficient estimation of the link function parameter in a robust Bayesian binary regression model," Computational Statistics & Data Analysis, Elsevier, vol. 73(C), pages 87-102.
    9. Jorge I. Figueroa-Zúñiga & Cristian L. Bayes & Víctor Leiva & Shuangzhe Liu, 2022. "Robust beta regression modeling with errors-in-variables: a Bayesian approach and numerical applications," Statistical Papers, Springer, vol. 63(3), pages 919-942, June.
    10. Eleanor McDonnell Feit & Mark A. Beltramo & Fred M. Feinberg, 2010. "Reality Check: Combining Choice Experiments with Market Data to Estimate the Importance of Product Attributes," Management Science, INFORMS, vol. 56(5), pages 785-800, May.
    11. Wu, Lang, 2007. "A computationally efficient method for nonlinear mixed-effects models with nonignorable missing data in time-varying covariates," Computational Statistics & Data Analysis, Elsevier, vol. 51(5), pages 2410-2419, February.
    12. Zhong, Peng & Huser, Raphaël & Opitz, Thomas, 2024. "Exact Simulation of Max-Infinitely Divisible Processes," Econometrics and Statistics, Elsevier, vol. 30(C), pages 96-109.
    13. Shen, Pao-sheng, 2015. "Conditional MLE for the proportional hazards model with left-truncated and interval-censored data," Statistics & Probability Letters, Elsevier, vol. 100(C), pages 164-171.
    14. Cai, Bo & Lin, Xiaoyan & Wang, Lianming, 2011. "Bayesian proportional hazards model for current status data with monotone splines," Computational Statistics & Data Analysis, Elsevier, vol. 55(9), pages 2644-2651, September.
    15. Samantha Leorato & Maura Mezzetti, 2015. "Spatial Panel Data Model with error dependence: a Bayesian Separable Covariance Approach," CEIS Research Paper 338, Tor Vergata University, CEIS, revised 09 Apr 2015.
    16. Griffin, J. E. & Steel, M. F. J., 2004. "Semiparametric Bayesian inference for stochastic frontier models," Journal of Econometrics, Elsevier, vol. 123(1), pages 121-152, November.
    17. Rana, Subrata & Roy, Surupa & Das, Kalyan, 2018. "Analysis of ordinal longitudinal data under nonignorable missingness and misreporting: An application to Alzheimer’s disease study," Journal of Multivariate Analysis, Elsevier, vol. 166(C), pages 62-77.
    18. Yang-Jin Kim, 2014. "Regression analysis of recurrent events data with incomplete observation gaps," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(7), pages 1619-1626, July.
    19. Takahiro Hoshino & Yuya Shimizu, 2019. "Doubly Robust-type Estimation of Population Moments and Parameters in Biased Sampling," Keio-IES Discussion Paper Series 2019-006, Institute for Economics Studies, Keio University.
    20. O’Neill, Donal, 2015. "Measuring obesity in the absence of a gold standard," Economics & Human Biology, Elsevier, vol. 17(C), pages 116-128.

    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:58:y:2002:i:1:p:98-109. 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.