IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v58y2002i2p305-315.html
   My bibliography  Save this article

Survival Analysis with Time-Varying Regression Effects Using a Tree-Based Approach

Author

Listed:
  • Ronghui Xu
  • Sudeshna Adak

Abstract

No abstract is available for this item.

Suggested Citation

  • Ronghui Xu & Sudeshna Adak, 2002. "Survival Analysis with Time-Varying Regression Effects Using a Tree-Based Approach," Biometrics, The International Biometric Society, vol. 58(2), pages 305-315, June.
    • Handle: RePEc:bla:biomet:v:58:y:2002:i:2:p:305-315
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/j.0006-341X.2002.00305.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. A. N. Pettitt & I. Bin Daud, 1990. "Investigating Time Dependence in Cox's Proportional Hazards Model," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 39(3), pages 313-329, November.
    2. J. A. Anderson & A. Senthilselvan, 1982. "A Two‐Step Regression Model for Hazard Functions," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 31(1), pages 44-51, March.
    3. Murphy, S. A. & Sen, P. K., 1991. "Time-dependent coefficients in a Cox-type regression model," Stochastic Processes and their Applications, Elsevier, vol. 39(1), pages 153-180, October.
    4. Chris T. Volinsky & Adrian E. Raftery, 2000. "Bayesian Information Criterion for Censored Survival Models," Biometrics, The International Biometric Society, vol. 56(1), pages 256-262, March.
    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. Youyi Fong & Chongzhi Di & Ying Huang & Peter B. Gilbert, 2017. "Model-robust inference for continuous threshold regression models," Biometrics, The International Biometric Society, vol. 73(2), pages 452-462, June.
    2. Marie-Therese Puth & Gerhard Tutz & Nils Heim & Eva Münster & Matthias Schmid & Moritz Berger, 2020. "Tree-based modeling of time-varying coefficients in discrete time-to-event models," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(3), pages 545-572, July.
    3. Xiaochun Li & Ronghui Xu, 2004. "Empirical and Kernel Estimation of Covariate Distribution Conditional on Survival Time," Harvard University Biostatistics Working Paper Series 1011, Berkeley Electronic Press.
    4. Kauermann, Goran & Xu, Ronghui & Vaida, Florin, 2008. "Stacked Laplace-EM algorithm for duration models with time-varying and random effects," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2514-2528, January.
    5. Li, Xiaochun & Xu, Ronghui, 2006. "Empirical and kernel estimation of covariate distribution conditional on survival time," Computational Statistics & Data Analysis, Elsevier, vol. 50(12), pages 3629-3643, August.

    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. John O'Quigley & Loki Natarajan, 2004. "Erosion of Regression Effect in a Survival Study," Biometrics, The International Biometric Society, vol. 60(2), pages 344-351, June.
    2. Ian W. McKeague & Mourad Tighiouart, 2000. "Bayesian Estimators for Conditional Hazard Functions," Biometrics, The International Biometric Society, vol. 56(4), pages 1007-1015, December.
    3. Anderl, Eva & Schumann, Jan Hendrik & Kunz, Werner, 2016. "Helping Firms Reduce Complexity in Multichannel Online Data: A New Taxonomy-Based Approach for Customer Journeys," Journal of Retailing, Elsevier, vol. 92(2), pages 185-203.
    4. Aurelija Burinskienė & Milena Seržantė, 2022. "Digitalisation as the Indicator of the Evidence of Sustainability in the European Union," Sustainability, MDPI, vol. 14(14), pages 1-20, July.
    5. Torben Martinussen & Christian Bressen Pipper, 2014. "Estimation of Causal Odds of Concordance using the Aalen Additive Model," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(1), pages 141-151, March.
    6. Mark S. Handcock & Adrian E. Raftery & Jeremy M. Tantrum, 2007. "Model‐based clustering for social networks," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(2), pages 301-354, March.
    7. Dimitris Korobilis & Kenichi Shimizu, 2022. "Bayesian Approaches to Shrinkage and Sparse Estimation," Foundations and Trends(R) in Econometrics, now publishers, vol. 11(4), pages 230-354, June.
    8. Malloy, Elizabeth J. & Spiegelman, Donna & Eisen, Ellen A., 2009. "Comparing measures of model selection for penalized splines in Cox models," Computational Statistics & Data Analysis, Elsevier, vol. 53(7), pages 2605-2616, May.
    9. Rezgar Zaki & Abbas Barabadi & Javad Barabady & Ali Nouri Qarahasanlou, 2022. "Observed and unobserved heterogeneity in failure data analysis," Journal of Risk and Reliability, , vol. 236(1), pages 194-207, February.
    10. Yanqing Sun & Rajeshwari Sundaram & Yichuan Zhao, 2009. "Empirical Likelihood Inference for the Cox Model with Time‐dependent Coefficients via Local Partial Likelihood," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 36(3), pages 444-462, September.
    11. Miao Han & Liuquan Sun & Yutao Liu & Jun Zhu, 2018. "Joint analysis of recurrent event data with additive–multiplicative hazards model for the terminal event time," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 81(5), pages 523-547, July.
    12. Gonzalo García-Donato & María Eugenia Castellanos & Alicia Quirós, 2021. "Bayesian Variable Selection with Applications in Health Sciences," Mathematics, MDPI, vol. 9(3), pages 1-16, January.
    13. Lee Kyu Ha & Chakraborty Sounak & Sun Jianguo, 2011. "Bayesian Variable Selection in Semiparametric Proportional Hazards Model for High Dimensional Survival Data," The International Journal of Biostatistics, De Gruyter, vol. 7(1), pages 1-32, April.
    14. Thomas H. Scheike & Mei-Jie Zhang, 2003. "Extensions and Applications of the Cox-Aalen Survival Model," Biometrics, The International Biometric Society, vol. 59(4), pages 1036-1045, December.
    15. Qu, Lianqiang & Song, Xinyuan & Sun, Liuquan, 2018. "Identification of local sparsity and variable selection for varying coefficient additive hazards models," Computational Statistics & Data Analysis, Elsevier, vol. 125(C), pages 119-135.
    16. Ungerer, Christina & Reuther, Kevin & Baltes, Guido, 2021. "The lingering living dead phenomenon: Distorting venture survival studies?," Journal of Business Venturing Insights, Elsevier, vol. 16(C).
    17. Laudicella, Mauro & Siciliani, Luigi & Cookson, Richard, 2012. "Waiting times and socioeconomic status: Evidence from England," Social Science & Medicine, Elsevier, vol. 74(9), pages 1331-1341.
    18. Boumezoued, Alexandre & Karoui, Nicole El & Loisel, Stéphane, 2017. "Measuring mortality heterogeneity with multi-state models and interval-censored data," Insurance: Mathematics and Economics, Elsevier, vol. 72(C), pages 67-82.
    19. Chu-Chih Chen & , Chuan-Pin Lee & Yuan-Horng Yan & Tsun-Jen Cheng & Pranab K. Sen, 2021. "A partial likelihood-based two-dimensional multistate markov model with application to myocardial infarction and stroke recurrence," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(2), pages 282-303, November.
    20. Bhattacharjee, A. & Samarjit Das, 2002. "Testing Proportionality in Duration Models with Respect to Continuous Covariates," Cambridge Working Papers in Economics 0220, Faculty of Economics, University of Cambridge.

    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:305-315. 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.