IDEAS home Printed from https://ideas.repec.org/a/spr/stabio/v10y2018i1d10.1007_s12561-017-9201-4.html
   My bibliography  Save this article

Second-Order Estimating Equations for Clustered Current Status Data from Family Studies Using Response-Dependent Sampling

Author

Listed:
  • Yujie Zhong

    (University of Cambridge, Cambridge Institute of Public Health)

  • Richard J. Cook

    (University of Waterloo)

Abstract

Studies about the genetic basis for disease are routinely conducted through family studies under response-dependent sampling in which affected individuals called probands are sampled from a disease registry, and their respective family members (non-probands) are recruited for study. The extent to which the dependence in some feature of the disease process (e.g., presence, age of onset, severity) varies according to the kinship of individuals reflects the evidence of a genetic cause for disease. When the probands are selected from a disease registry, it is common for them to provide quite detailed information regarding their disease history, but non-probands often simply provide their disease status at the time of contact. We develop conditional second-order estimating equations for studying the nature and extent of within-family dependence which recognizes the biased sampling scheme employed in family studies and the current status data provided by the non-probands. Simulation studies are carried out to evaluate the finite sample performance of different estimating functions and to quantify the empirical relative efficiency of the various methods. Sensitivity to model misspecification is also explored. An application to a motivating psoriatic arthritis family study is given for illustration.

Suggested Citation

  • Yujie Zhong & Richard J. Cook, 2018. "Second-Order Estimating Equations for Clustered Current Status Data from Family Studies Using Response-Dependent Sampling," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 10(1), pages 160-183, April.
  • Handle: RePEc:spr:stabio:v:10:y:2018:i:1:d:10.1007_s12561-017-9201-4
    DOI: 10.1007/s12561-017-9201-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12561-017-9201-4
    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/s12561-017-9201-4?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Nilanjan Chatterjee & Zeynep Kalaylioglu & Joanna H. Shih & Mitchell H. Gail, 2006. "Case–Control and Case-Only Designs with Genotype and Family History Data: Estimating Relative Risk, Residual Familial Aggregation, and Cumulative Risk," Biometrics, The International Biometric Society, vol. 62(1), pages 36-48, March.
    2. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
    3. Malka Gorfine & Li Hsu, 2011. "Frailty-Based Competing Risks Model for Multivariate Survival Data," Biometrics, The International Biometric Society, vol. 67(2), pages 415-426, June.
    4. Malka Gorfine* & Li Hsu* & Giovanni Parmigiani, 2013. "Frailty Models for Familial Risk With Application to Breast Cancer," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(504), pages 1205-1215, December.
    5. Nicholas P. Jewell & Mark van der Laan & Xiudong Lei, 2005. "Bivariate current status data with univariate monitoring times," Biometrika, Biometrika Trust, vol. 92(4), pages 847-862, December.
    6. David B. Dunson & Gregg E. Dinse, 2002. "Bayesian Models for Multivariate Current Status Data with Informative Censoring," Biometrics, The International Biometric Society, vol. 58(1), pages 79-88, March.
    7. Joanna H. Shih & Paul S. Albert, 2010. "Modeling Familial Association of Ages at Onset of Disease in the Presence of Competing Risk," Biometrics, The International Biometric Society, vol. 66(4), pages 1012-1023, December.
    8. Joanna H. Shih & Nilanjan Chatterjee, 2002. "Analysis of Survival Data from Case–Control Family Studies," Biometrics, The International Biometric Society, vol. 58(3), pages 502-509, September.
    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. Fei Jiang & Sebastien Haneuse, 2017. "A Semi-parametric Transformation Frailty Model for Semi-competing Risks Survival Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(1), pages 112-129, March.
    2. Hao Liu & Jing Qin, 2018. "Semiparametric probit models with univariate and bivariate current†status data," Biometrics, The International Biometric Society, vol. 74(1), pages 68-76, March.
    3. P.A.V.B. Swamy & I-Lok Chang & Jatinder S. Mehta & William H. Greene & Stephen G. Hall & George S. Tavlas, 2016. "Removing Specification Errors from the Usual Formulation of Binary Choice Models," Econometrics, MDPI, vol. 4(2), pages 1-21, June.
    4. Lu Chen & Li Hsu & Kathleen Malone, 2009. "A Frailty-Model-Based Approach to Estimating the Age-Dependent Penetrance Function of Candidate Genes Using Population-Based Case-Control Study Designs: An Application to Data on the BRCA1 Gene," Biometrics, The International Biometric Society, vol. 65(4), pages 1105-1114, December.
    5. Carlo Altavilla & Raffaella Giacomini & Giuseppe Ragusa, 2017. "Anchoring the yield curve using survey expectations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(6), pages 1055-1068, September.
    6. Fernando Rios-Avila & Gustavo Canavire-Bacarreza, 2018. "Standard-error correction in two-stage optimization models: A quasi–maximum likelihood estimation approach," Stata Journal, StataCorp LLC, vol. 18(1), pages 206-222, March.
    7. Sandy Fréret & Denis Maguain, 2017. "The effects of agglomeration on tax competition: evidence from a two-regime spatial panel model on French data," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 24(6), pages 1100-1140, December.
    8. Ai, Chunrong & Chen, Xiaohong, 2007. "Estimation of possibly misspecified semiparametric conditional moment restriction models with different conditioning variables," Journal of Econometrics, Elsevier, vol. 141(1), pages 5-43, November.
    9. Gregory, Allan W. & McCurdy, Thomas H., 1986. "The unbiasedness hypothesis in the forward foreign exchange market: A specification analysis with application to France, Italy, Japan, the United Kingdom and West Germany," European Economic Review, Elsevier, vol. 30(2), pages 365-381, April.
    10. B. Praag & T. Dijkstra & J. Velzen, 1985. "Least-squares theory based on general distributional assumptions with an application to the incomplete observations problem," Psychometrika, Springer;The Psychometric Society, vol. 50(1), pages 25-36, March.
    11. Reischmann, Markus, 2016. "Creative accounting and electoral motives: Evidence from OECD countries," Journal of Comparative Economics, Elsevier, vol. 44(2), pages 243-257.
    12. Czudaj Robert L., 2020. "The role of uncertainty on agricultural futures markets momentum trading and volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(3), pages 1-39, June.
    13. Vassilios Babalos & Mehmet Balcilar & Rangan Gupta, 2014. "Revisiting Herding Behavior in REITs: A Regime-Switching Approach," Working Papers 201448, University of Pretoria, Department of Economics.
    14. Topi Miettinen & Sigrid Suetens, 2008. "Communication and Guilt in a Prisoner's Dilemma," Journal of Conflict Resolution, Peace Science Society (International), vol. 52(6), pages 945-960, December.
    15. Towfiqul Islam Khan & Mashfique Ibne Akbar, 2015. "Illicit Financial Flow in view of Financing the Post-2015 Development Agenda," Southern Voice Occasional Paper 25, Southern Voice.
    16. Catherine Doz & Domenico Giannone & Lucrezia Reichlin, 2012. "A Quasi–Maximum Likelihood Approach for Large, Approximate Dynamic Factor Models," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1014-1024, November.
    17. Potrafke, Niklas, 2019. "Electoral cycles in perceived corruption: International empirical evidence," Journal of Comparative Economics, Elsevier, vol. 47(1), pages 215-224.
    18. Corradi, Valentina & Swanson, Norman R., 2004. "A test for the distributional comparison of simulated and historical data," Economics Letters, Elsevier, vol. 85(2), pages 185-193, November.
    19. Hendrik Thiel & Stephan L. Thomsen, 2015. "Individual Poverty Paths and the Stability of Control-Perception," SOEPpapers on Multidisciplinary Panel Data Research 794, DIW Berlin, The German Socio-Economic Panel (SOEP).
    20. Arzheimer, Kai & Evans, Jocelyn, 2010. "Bread and butter à la française: Multiparty forecasts of the French legislative vote (1981-2007)," International Journal of Forecasting, Elsevier, vol. 26(1), pages 19-31, January.

    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:stabio:v:10:y:2018:i:1:d:10.1007_s12561-017-9201-4. 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.