IDEAS home Printed from https://ideas.repec.org/a/bla/jorssc/v58y2009i5p577-600.html
   My bibliography  Save this article

Stability analysis of an additive spline model for respiratory health data by using knot removal

Author

Listed:
  • Harald Binder
  • Willi Sauerbrei

Abstract

In many settings with possibly non-linear influence of covariates, such as in the present application with children's respiratory health data, generalized additive models are an attractive choice. Although techniques for fitting these have been extensively investigated, there are fewer results on stability of replication, i.e. stability of fitted model components with respect to perturbations in the data. Nevertheless, this aspect is essential for judging how useful the present model is for understanding predictors of lung function. We therefore investigate existing tools for stability analysis based on bootstrap samples, such as quantities for variability and bias, for our application. Furthermore, as the focus is on models based on "B"-splines, knot removal techniques are available. These can help to provide more insight into the stability of local features that are fitted in bootstrap samples. We analyse the bootstrap result matrix via log-linear models. Specifically, the relationship with respect to local features between the influence functions of potential lung function predictors is investigated. Copyright (c) 2009 Royal Statistical Society.

Suggested Citation

  • Harald Binder & Willi Sauerbrei, 2009. "Stability analysis of an additive spline model for respiratory health data by using knot removal," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 58(5), pages 577-600.
  • Handle: RePEc:bla:jorssc:v:58:y:2009:i:5:p:577-600
    as

    Download full text from publisher

    File URL: http://www.blackwell-synergy.com/doi/abs/10.1111/j.1467-9876.2009.00668.x
    File Function: link to full text
    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. Ruppert,David & Wand,M. P. & Carroll,R. J., 2003. "Semiparametric Regression," Cambridge Books, Cambridge University Press, number 9780521785167, April.
    2. Breiman, Leo, 1993. "Fitting additive models to regression data : Diagnostics and alternative views," Computational Statistics & Data Analysis, Elsevier, vol. 15(1), pages 13-46, January.
    3. Binder, Harald & Sauerbrei, Willi, 2008. "Increasing the usefulness of additive spline models by knot removal," Computational Statistics & Data Analysis, Elsevier, vol. 52(12), pages 5305-5318, August.
    4. Willi Sauerbrei, 1999. "The Use of Resampling Methods to Simplify Regression Models in Medical Statistics," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 48(3), pages 313-329.
    5. Simon N. Wood, 2004. "Stable and Efficient Multiple Smoothing Parameter Estimation for Generalized Additive Models," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 673-686, January.
    6. Ruppert,David & Wand,M. P. & Carroll,R. J., 2003. "Semiparametric Regression," Cambridge Books, Cambridge University Press, number 9780521780506, April.
    7. W. Sauerbrei & P. Royston, 1999. "Building multivariable prognostic and diagnostic models: transformation of the predictors by using fractional polynomials," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 162(1), pages 71-94.
    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. Patrick Royston & Willi Sauerbrei, 2009. "Bootstrap assessment of the stability of multivariable models," Stata Journal, StataCorp LP, vol. 9(4), pages 547-570, December.

    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:jorssc:v:58:y:2009:i:5:p:577-600. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley-Blackwell Digital Licensing) or (Christopher F. Baum). General contact details of provider: http://edirc.repec.org/data/rssssea.html .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.