IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v58y2002i2p287-297.html
   My bibliography  Save this article

Modeling Spatial Survival Data Using Semiparametric Frailty Models

Author

Listed:
  • Yi Li
  • Louise Ryan

Abstract

No abstract is available for this item.

Suggested Citation

  • Yi Li & Louise Ryan, 2002. "Modeling Spatial Survival Data Using Semiparametric Frailty Models," Biometrics, The International Biometric Society, vol. 58(2), pages 287-297, June.
    • Handle: RePEc:bla:biomet:v:58:y:2002:i:2:p:287-297
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/j.0006-341X.2002.00287.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. Samuli Ripatti & Juni Palmgren, 2000. "Estimation of Multivariate Frailty Models Using Penalized Partial Likelihood," Biometrics, The International Biometric Society, vol. 56(4), pages 1016-1022, 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. Cizek, P. & Lei, J. & Ligthart, J.E., 2012. "The Determinants of VAT Introduction : A Spatial Duration Analysis," Other publications TiSEM 835efbcb-4537-4dab-aaa3-c, Tilburg University, School of Economics and Management.
    2. Akim Adekpedjou & Sophie Dabo‐Niang, 2021. "Semiparametric estimation with spatially correlated recurrent events," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(4), pages 1097-1126, December.
    3. Taylor, Benjamin M. & Rowlingson, Barry S., 2017. "spatsurv: An R Package for Bayesian Inference with Spatial Survival Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 77(i04).
    4. Pavel Čížek & Jinghua Lei & Jenny E. Ligthart, 2017. "Do Neighbours Influence Value-Added-Tax Introduction? A Spatial Duration Analysis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(1), pages 25-54, February.
    5. Wolter, James Lewis, 2016. "Kernel estimation of hazard functions when observations have dependent and common covariates," Journal of Econometrics, Elsevier, vol. 193(1), pages 1-16.
    6. F. S. Nathoo & C. B. Dean, 2008. "Spatial Multistate Transitional Models for Longitudinal Event Data," Biometrics, The International Biometric Society, vol. 64(1), pages 271-279, March.
    7. Jiajia Zhang & Andrew B. Lawson, 2011. "Bayesian parametric accelerated failure time spatial model and its application to prostate cancer," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(3), pages 591-603, November.
    8. Paciorek, Christopher J., 2007. "Computational techniques for spatial logistic regression with large data sets," Computational Statistics & Data Analysis, Elsevier, vol. 51(8), pages 3631-3653, May.
    9. S. Magnussen, 2015. "A fixed count sampling estimator of stem density based on a survival function," Journal of Forest Science, Czech Academy of Agricultural Sciences, vol. 61(11), pages 485-495.
    10. James Wolter, 2015. "Kernel Estimation Of Hazard Functions When Observations Have Dependent and Common Covariates," Economics Series Working Papers 761, University of Oxford, Department of Economics.
    11. Paik, Jane & Ying, Zhiliang, 2012. "A composite likelihood approach for spatially correlated survival data," Computational Statistics & Data Analysis, Elsevier, vol. 56(1), pages 209-216, January.
    12. James Wolter, 2013. "Separating the impact of macroeconomic variables and global frailty in event data," Economics Series Working Papers 667, University of Oxford, Department of Economics.
    13. Carroll, Rachel & Lawson, Andrew B. & Jackson, Chandra L. & Zhao, Shanshan, 2017. "Assessment of spatial variation in breast cancer-specific mortality using Louisiana SEER data," Social Science & Medicine, Elsevier, vol. 193(C), pages 1-7.
    14. Lan Huang & Martin Kulldorff & David Gregorio, 2007. "A Spatial Scan Statistic for Survival Data," Biometrics, The International Biometric Society, vol. 63(1), pages 109-118, March.
    15. K. Motarjem & M. Mohammadzadeh & A. Abyar, 2020. "Geostatistical survival model with Gaussian random effect," Statistical Papers, Springer, vol. 61(1), pages 85-107, February.
    16. Haiming Zhou & Timothy Hanson & Jiajia Zhang, 2017. "Generalized accelerated failure time spatial frailty model for arbitrarily censored data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(3), pages 495-515, July.
    17. Fathima Z. Sainul Abdeen & Akim Adekpedjou & Sophie Dabo Niang, 2024. "Statistical Modeling of Right-Censored Spatial Data Using Gaussian Random Fields," Mathematics, MDPI, vol. 12(10), pages 1-23, 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. Il Do Ha & Maengseok Noh & Youngjo Lee, 2010. "Bias Reduction of Likelihood Estimators in Semiparametric Frailty Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 37(2), pages 307-320, June.
    2. Peng, Mengjiao & Xiang, Liming & Wang, Shanshan, 2018. "Semiparametric regression analysis of clustered survival data with semi-competing risks," Computational Statistics & Data Analysis, Elsevier, vol. 124(C), pages 53-70.
    3. Andreas Wienke & Konstantin G. Arbeev & Isabella Locatelli & Anatoli I. Yashin, 2003. "A simulation study of different correlated frailty models and estimation strategies," MPIDR Working Papers WP-2003-018, Max Planck Institute for Demographic Research, Rostock, Germany.
    4. George, Morris & Kumar, V. & Grewal, Dhruv, 2013. "Maximizing Profits for a Multi-Category Catalog Retailer," Journal of Retailing, Elsevier, vol. 89(4), pages 374-396.
    5. Guillaume Horny & Dragana Djurdjevic & Bernhard Boockmann & François Laisney, 2008. "Bayesian Estimation of Cox Models with Non-nested Random Effects: an Application to the Ratification Of ILO Conventions by Developing Countries," Annals of Economics and Statistics, GENES, issue 89, pages 193-214.
    6. Goele Massonnet & Paul Janssen & Tomasz Burzykowski, 2008. "Fitting Conditional Survival Models to Meta‐Analytic Data by Using a Transformation Toward Mixed‐Effects Models," Biometrics, The International Biometric Society, vol. 64(3), pages 834-842, September.
    7. Jing Wang, 2019. "Weighted estimation for multivariate shared frailty models for complex surveys," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 25(3), pages 469-479, July.
    8. Dragana Cvijanović & Stanimira Milcheva & Alex Minne, 2022. "Preferences of Institutional Investors in Commercial Real Estate," The Journal of Real Estate Finance and Economics, Springer, vol. 65(2), pages 321-359, August.
    9. Jaeun Choi & Jianwen Cai & Donglin Zeng, 2017. "Penalized Likelihood Approach for Simultaneous Analysis of Survival Time and Binary Longitudinal Outcome," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 79(2), pages 190-216, November.
    10. Sukhmani Sidhu & Kanchan Jain & Suresh Kumar Sharma, 2018. "Bayesian estimation of generalized gamma shared frailty model," Computational Statistics, Springer, vol. 33(1), pages 277-297, March.
    11. Yu, Binbing, 2006. "Estimation of shared Gamma frailty models by a modified EM algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 50(2), pages 463-474, January.
    12. Wenjing Qi & Andrew S Allen & Yi-Ju Li, 2019. "Family-based association tests for rare variants with censored traits," PLOS ONE, Public Library of Science, vol. 14(1), pages 1-17, January.
    13. Zhangsheng Yu & Xihong Lin & Wanzhu Tu, 2012. "Semiparametric Frailty Models for Clustered Failure Time Data," Biometrics, The International Biometric Society, vol. 68(2), pages 429-436, June.
    14. Djeundje, Viani Biatat & Crook, Jonathan, 2018. "Incorporating heterogeneity and macroeconomic variables into multi-state delinquency models for credit cards," European Journal of Operational Research, Elsevier, vol. 271(2), pages 697-709.
    15. Andreas Groll & Trevor Hastie & Gerhard Tutz, 2017. "Selection of effects in Cox frailty models by regularization methods," Biometrics, The International Biometric Society, vol. 73(3), pages 846-856, September.
    16. Il Do Ha & Liming Xiang & Mengjiao Peng & Jong-Hyeon Jeong & Youngjo Lee, 2020. "Frailty modelling approaches for semi-competing risks data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(1), pages 109-133, January.
    17. Sharif Mahmood & Begum Zainab & A.H.M. Mahbub Latif, 2013. "Frailty modeling for clustered survival data: an application to birth interval in Bangladesh," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(12), pages 2670-2680, December.
    18. Mitra Rahimzadeh & Ebrahim Hajizadeh & Farzad Eskandari, 2011. "Non-mixture cure correlated frailty models in Bayesian approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(8), pages 1651-1663, August.
    19. Zeng, Zhiguo & Barros, Anne & Coit, David, 2023. "Dependent failure behavior modeling for risk and reliability: A systematic and critical literature review," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
    20. Richard Tawiah & Geoffrey J. McLachlan & Shu Kay Ng, 2020. "A bivariate joint frailty model with mixture framework for survival analysis of recurrent events with dependent censoring and cure fraction," Biometrics, The International Biometric Society, vol. 76(3), pages 753-766, September.

    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:2:p:287-297. 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.