IDEAS home Printed from https://ideas.repec.org/a/bla/jorssa/v169y2006i3p493-505.html
   My bibliography  Save this article

Linkage bias in estimating the association between childhood exposures and propensity to become a mother: an example of simple sensitivity analyses

Author

Listed:
  • D. Nitsch
  • B. L. DeStavola
  • S. M. B. Morton
  • D. A. Leon

Abstract

Summary. Record linkage is a powerful tool to obtain individual follow‐up information that is held in routinely collected databases. However, this method is potentially limited not only by the quality of the original data but also by the temporal and geographic coverage of the routine data. Migration in particular is a factor that might introduce systematic bias even in analyses of data covering relatively large geographical areas. We describe a linkage application where emigration bias might be an issue and use the sensitivity analysis approach that has been described by Molenberghs and co‐workers and Kenward and co‐workers to assess the extent of this bias.

Suggested Citation

  • D. Nitsch & B. L. DeStavola & S. M. B. Morton & D. A. Leon, 2006. "Linkage bias in estimating the association between childhood exposures and propensity to become a mother: an example of simple sensitivity analyses," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(3), pages 493-505, July.
  • Handle: RePEc:bla:jorssa:v:169:y:2006:i:3:p:493-505
    DOI: 10.1111/j.1467-985X.2006.00400.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1467-985X.2006.00400.x
    Download Restriction: no

    File URL: https://libkey.io/10.1111/j.1467-985X.2006.00400.x?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
    ---><---

    References listed on IDEAS

    as
    1. Geert Verbeke & Geert Molenberghs & Herbert Thijs & Emmanuel Lesaffre & Michael G. Kenward, 2001. "Sensitivity Analysis for Nonrandom Dropout: A Local Influence Approach," Biometrics, The International Biometric Society, vol. 57(1), pages 7-14, March.
    2. Charles F. Manski, 1989. "Anatomy of the Selection Problem," Journal of Human Resources, University of Wisconsin Press, vol. 24(3), pages 343-360.
    3. Daniel O. Scharfstein & Charles F. Manski & James C. Anthony, 2004. "On the Construction of Bounds in Prospective Studies with Missing Ordinal Outcomes: Application to the Good Behavior Game Trial," Biometrics, The International Biometric Society, vol. 60(1), pages 154-164, March.
    4. Geert Molenberghs & Michael G. Kenward & Els Goetghebeur, 2001. "Sensitivity analysis for incomplete contingency tables: the Slovenian plebiscite case," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 50(1), pages 15-29.
    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. Caroline Beunckens & Cristina Sotto & Geert Molenberghs & Geert Verbeke, 2009. "A multifaceted sensitivity analysis of the Slovenian public opinion survey data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 58(2), pages 171-196, May.
    2. Baojiang Chen & Xiao-Hua Zhou, 2011. "Doubly Robust Estimates for Binary Longitudinal Data Analysis with Missing Response and Missing Covariates," Biometrics, The International Biometric Society, vol. 67(3), pages 830-842, September.
    3. Ivy Jansen & Geert Molenberghs, 2008. "A flexible marginal modelling strategy for non‐monotone missing data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(2), pages 347-373, April.
    4. D. Todem & J. Fine & L. Peng, 2010. "A Global Sensitivity Test for Evaluating Statistical Hypotheses with Nonidentifiable Models," Biometrics, The International Biometric Society, vol. 66(2), pages 558-566, June.
    5. Ivy Jansen & Geert Molenberghs & Marc Aerts & Herbert Thijs & Kristel Van Steen, 2003. "A Local Influence Approach Applied to Binary Data from a Psychiatric Study," Biometrics, The International Biometric Society, vol. 59(2), pages 410-419, June.
    6. Ivy Jansen & Ann Van den Troost & Geert Molenberghs & Ad A. Vermulst & Jan R. M. Gerris, 2006. "Modeling Partially Incomplete Marital Satisfaction Data," Sociological Methods & Research, , vol. 35(1), pages 113-136, August.
    7. Rhoads Christopher H., 2012. "Problems with Tests of the Missingness Mechanism in Quantitative Policy Studies," Statistics, Politics and Policy, De Gruyter, vol. 3(1), pages 1-25, March.
    8. Victor Aguirregabiria, 2006. "Another Look at the Identification of Dynamic Discrete Decision Processes: With an Application to Retirement Behavior," 2006 Meeting Papers 169, Society for Economic Dynamics.
    9. Lanot, Gauthier & Walker, Ian, 1998. "The union/non-union wage differential: An application of semi-parametric methods," Journal of Econometrics, Elsevier, vol. 84(2), pages 327-349, June.
    10. Christian Bontemps & Thierry Magnac & Eric Maurin, 2012. "Set Identified Linear Models," Econometrica, Econometric Society, vol. 80(3), pages 1129-1155, May.
    11. Stefan Boes, 2013. "Nonparametric analysis of treatment effects in ordered response models," Empirical Economics, Springer, vol. 44(1), pages 81-109, February.
    12. Jiannan Lu & Peng Ding & Tirthankar Dasgupta, 2018. "Treatment Effects on Ordinal Outcomes: Causal Estimands and Sharp Bounds," Journal of Educational and Behavioral Statistics, , vol. 43(5), pages 540-567, October.
    13. Vikesh Amin & Jere R. Behrman & Jason M. Fletcher & Carlos A. Flores & Alfonso Flores-Lagunes & Hans-Peter Kohler, 2022. "Does Schooling Improve Cognitive Abilities at Older Ages: Causal Evidence from Nonparametric Bounds," PIER Working Paper Archive 22-016, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    14. Manski, Charles, 1994. "Simultaneity with Downward Sloping Demand," SFB 373 Discussion Papers 1994,29, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    15. van der Klaauw, Bas & Koning, Ruud H, 2003. "Testing the Normality Assumption in the Sample Selection Model with an Application to Travel Demand," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(1), pages 31-42, January.
    16. Giorgio Brunello & Dimitris Christelis & Anna Sanz‐de‐Galdeano & Anastasia Terskaya, 2024. "Does college selectivity reduce obesity? A partial identification approach," Health Economics, John Wiley & Sons, Ltd., vol. 33(10), pages 2306-2320, October.
    17. Mullahy, John, 2024. "Analyzing health outcomes measured as bounded counts," Journal of Health Economics, Elsevier, vol. 95(C).
    18. van Soest, Arthur & Hurd, Michael, 2008. "A Test for Anchoring and Yea-Saying in Experimental Consumption Data," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 126-136, March.
    19. Wiedner, Jonas & Giesecke, Johannes, 2022. "Immigrant Men’s Economic Adaptation in Changing Labor Markets: Why Gaps between Turkish and German Men Expanded, 1976–2015," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 56(1), pages 176-205.
    20. Breunig, Christoph & Mammen, Enno & Simoni, Anna, 2018. "Nonparametric estimation in case of endogenous selection," Journal of Econometrics, Elsevier, vol. 202(2), pages 268-285.

    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:jorssa:v:169:y:2006:i:3:p:493-505. 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: https://edirc.repec.org/data/rssssea.html .

    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.