IDEAS home Printed from https://ideas.repec.org/a/spr/lifeda/v27y2021i2d10.1007_s10985-020-09512-2.html
   My bibliography  Save this article

Optimal designs for discrete-time survival models with random effects

Author

Listed:
  • Xiao-Dong Zhou

    (Shanghai University of International Business and Economics)

  • Yun-Juan Wang

    (Shanghai Lixin University Accounting and Finance)

  • Rong-Xian Yue

    (Shanghai Normal University)

Abstract

This paper considers the optimal design for the frailty model with discrete-time survival endpoints in longitudinal studies. We introduce the random effects into the discrete hazard models to account for the heterogeneity between experimental subjects, which causes the observations of the same subject at the sequential time points being correlated. We propose a general design method to collect the survival endpoints as inexpensively and efficiently as possible. A cost-based generalized D ( $$D_s$$ D s )-optimal design criterion is proposed to derive the optimal designs for estimating the fixed effects with cost constraint. Different computation strategies based on grid search or particle swarm optimization (PSO) algorithm are provided to obtain generalized D ( $$D_s$$ D s )-optimal designs. The equivalence theorem for the cost-based D ( $$D_s$$ D s )-optimal design criterion is given to verify the optimality of the designs. Our numerical results indicate that the presence of the random effects has a great influence on the optimal designs. Some useful suggestions are also put forward for future designing longitudinal studies.

Suggested Citation

  • Xiao-Dong Zhou & Yun-Juan Wang & Rong-Xian Yue, 2021. "Optimal designs for discrete-time survival models with random effects," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 27(2), pages 300-332, April.
    • Handle: RePEc:spr:lifeda:v:27:y:2021:i:2:d:10.1007_s10985-020-09512-2
    DOI: 10.1007/s10985-020-09512-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10985-020-09512-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10985-020-09512-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Ueckert, Sebastian & Mentré, France, 2017. "A new method for evaluation of the Fisher information matrix for discrete mixed effect models using Monte Carlo sampling and adaptive Gaussian quadrature," Computational Statistics & Data Analysis, Elsevier, vol. 111(C), pages 203-219.
    2. Andreas Groll & Gerhard Tutz, 2017. "Variable selection in discrete survival models including heterogeneity," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(2), pages 305-338, April.
    3. Xiao-Dong Zhou & Yun-Juan Wang & Rong-Xian Yue, 2018. "Robust population designs for longitudinal linear regression model with a random intercept," Computational Statistics, Springer, vol. 33(2), pages 903-931, June.
    4. Maryam Safarkhani & Mirjam Moerbeek, 2016. "D-optimal designs for a continuous predictor in longitudinal trials with discrete-time survival endpoints," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 70(2), pages 146-171, May.
    5. Mullen, Katharine M., 2014. "Continuous Global Optimization in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 60(i06).
    6. T. W. Waite & D. C. Woods, 2015. "Designs for generalized linear models with random block effects via information matrix approximations," Biometrika, Biometrika Trust, vol. 102(3), pages 677-693.
    7. Sheng Wu & Weng Kee Wong & Catherine M. Crespi, 2017. "Maximin optimal designs for cluster randomized trials," Biometrics, The International Biometric Society, vol. 73(3), pages 916-926, September.
    8. Nicoletti, Cheti & Rondinelli, Concetta, 2010. "The (mis)specification of discrete duration models with unobserved heterogeneity: A Monte Carlo study," Journal of Econometrics, Elsevier, vol. 159(1), pages 1-13, November.
    9. Safarkhani, Maryam & Moerbeek, Mirjam, 2014. "The influence of a covariate on optimal designs in longitudinal studies with discrete-time survival endpoints," Computational Statistics & Data Analysis, Elsevier, vol. 75(C), pages 217-226.
    10. Jóźwiak, Katarzyna & Moerbeek, Mirjam, 2012. "Cost-effective designs for trials with discrete-time survival endpoints," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 2086-2096.
    11. Abebe, Haftom T. & Tan, Frans E.S. & Van Breukelen, Gerard J.P. & Berger, Martijn P.F., 2014. "Bayesian D-optimal designs for the two parameter logistic mixed effects model," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 1066-1076.
    12. Tekle, Fetene B. & Tan, Frans E.S. & Berger, Martijn P.F., 2008. "Maximin D-optimal designs for binary longitudinal responses," Computational Statistics & Data Analysis, Elsevier, vol. 52(12), pages 5253-5262, August.
    Full references (including those not matched with items on IDEAS)

    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. Ueckert, Sebastian & Mentré, France, 2017. "A new method for evaluation of the Fisher information matrix for discrete mixed effect models using Monte Carlo sampling and adaptive Gaussian quadrature," Computational Statistics & Data Analysis, Elsevier, vol. 111(C), pages 203-219.
    2. Hong-Yan Jiang & Rong-Xian Yue, 2019. "Pseudo-Bayesian D-optimal designs for longitudinal Poisson mixed models with correlated errors," Computational Statistics, Springer, vol. 34(1), pages 71-87, March.
    3. Francesca Modena & Concetta Rondinelli, 2011. "Leaving home and housing prices. The experience of Italian youth emancipation," Department of Economics Working Papers 1101, Department of Economics, University of Trento, Italia.
    4. Fetene B. Tekle & Dereje W. Gudicha & Jeroen K. Vermunt, 2016. "Power analysis for the bootstrap likelihood ratio test for the number of classes in latent class models," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 10(2), pages 209-224, June.
    5. Mussida Chiara & Sciulli Dario, 2015. "Flexibility Policies and Re-employment Probabilities in Italy," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 15(2), pages 621-651, April.
    6. Damien Rousselière, 2019. "A Flexible Approach to Age Dependence in Organizational Mortality: Comparing the Life Duration for Cooperative and Non-Cooperative Enterprises Using a Bayesian Generalized Additive Discrete Time Survi," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 17(4), pages 829-855, December.
    7. Laha, A. K. & Rathi, Poonam, 2017. "Are the temperature of Indian cities Increasing?: Some Insights Using Change Point Analysis with Functional Data," IIMA Working Papers WP 2017-08-03, Indian Institute of Management Ahmedabad, Research and Publication Department.
    8. Hess Wolfgang & Tutz Gerhard & Gertheiss Jan, 2016. "A Flexible Link Function for Discrete-Time Duration Models," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 236(4), pages 455-481, August.
    9. Ron Boschma & Riccardo Cappelli & Anet Weterings, 2017. "Labour mobility, skill-relatedness and plant survival over the industry life cycle: Evidence from new Dutch plants," Papers in Evolutionary Economic Geography (PEEG) 1731, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Dec 2017.
    10. Andreas Groll & Gerhard Tutz, 2017. "Variable selection in discrete survival models including heterogeneity," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(2), pages 305-338, April.
    11. Mircea Trandafir, 2014. "The Effect of Same-Sex Marriage Laws on Different-Sex Marriage: Evidence From the Netherlands," Demography, Springer;Population Association of America (PAA), vol. 51(1), pages 317-340, February.
    12. Hess, Wolfgang & Persson, Maria, 2010. "The Duration of Trade Revisited. Continuous-Time vs. Discrete-Time Hazards," Working Papers 2010:1, Lund University, Department of Economics.
    13. Erik Scherpf & Benjamin Cerf, 2019. "Local Labor Demand and Program Participation Dynamics: Evidence from New York SNAP Administrative Records," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 38(2), pages 394-425, March.
    14. Rossella Iraci Capuccinello, 2014. "Determinants and timing of dropping out decisions: evidence from the UK FE sector," Working Papers 15742191, Lancaster University Management School, Economics Department.
    15. Helmut Farbmacher & Harald Tauchmann, 2023. "Linear fixed-effects estimation with nonrepeated outcomes," Econometric Reviews, Taylor & Francis Journals, vol. 42(8), pages 635-654, September.
    16. 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.
    17. Sameh Abdulah & Yuxiao Li & Jian Cao & Hatem Ltaief & David E. Keyes & Marc G. Genton & Ying Sun, 2023. "Large‐scale environmental data science with ExaGeoStatR," Environmetrics, John Wiley & Sons, Ltd., vol. 34(1), February.
    18. Ronald Hagan & Andrew M. Jones & Nigel Rice, 2009. "Health and Retirement in Europe," IJERPH, MDPI, vol. 6(10), pages 1-20, October.
    19. Wiens, Douglas P., 2010. "Robustness of design for the testing of lack of fit and for estimation in binary response models," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 3371-3378, December.
    20. Hugo Castro-Silva & Francisco Lima, 2023. "The struggle of small firms to retain high-skill workers: job duration and the importance of knowledge intensity," Small Business Economics, Springer, vol. 60(2), pages 537-572, February.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:spr:lifeda:v:27:y:2021:i:2:d:10.1007_s10985-020-09512-2. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.