IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v59y2003i4p1158-1169.html
   My bibliography  Save this article

Semiparametric Regression Splines in Matched Case-Control Studies

Author

Listed:
  • Inyoung Kim
  • Noah D. Cohen
  • Raymond J. Carroll

Abstract

No abstract is available for this item.

Suggested Citation

  • Inyoung Kim & Noah D. Cohen & Raymond J. Carroll, 2003. "Semiparametric Regression Splines in Matched Case-Control Studies," Biometrics, The International Biometric Society, vol. 59(4), pages 1158-1169, December.
    • Handle: RePEc:bla:biomet:v:59:y:2003:i:4:p:1158-1169
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/j.0006-341X.2003.00133.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. Brent A. Coull & David Ruppert & M. P. Wand, 2001. "Simple Incorporation of Interactions into Additive Models," Biometrics, The International Biometric Society, vol. 57(2), pages 539-545, June.
    2. M. C. Paik & R. L. Sacco, 2000. "Matched case–control data analyses with missing covariates," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 49(1), pages 145-156.
    3. Glen A. Satten & Raymond J. Carroll, 2000. "Conditional and Unconditional Categorical Regression Models with Missing Covariates," Biometrics, The International Biometric Society, vol. 56(2), pages 384-388, June.
    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. Heng Chen & Daniel F. Heitjan, 2022. "Analysis of local sensitivity to nonignorability with missing outcomes and predictors," Biometrics, The International Biometric Society, vol. 78(4), pages 1342-1352, December.
    2. Liu, Tianqing & Yuan, Xiaohui & Li, Zhaohai & Li, Yuanzhang, 2013. "Empirical and weighted conditional likelihoods for matched case-control studies with missing covariates," Journal of Multivariate Analysis, Elsevier, vol. 119(C), pages 185-199.
    3. Samiran Sinha & Tapabrata Maiti, 2008. "Analysis of Matched Case–Control Data in Presence of Nonignorable Missing Exposure," Biometrics, The International Biometric Society, vol. 64(1), pages 106-114, March.
    4. Jaeil Ahn & Bhramar Mukherjee & Stephen B. Gruber & Samiran Sinha, 2011. "Missing Exposure Data in Stereotype Regression Model: Application to Matched Case–Control Study with Disease Subclassification," Biometrics, The International Biometric Society, vol. 67(2), pages 546-558, June.
    5. Myunghee Cho Paik, 2004. "Nonignorable Missingness in Matched Case–Control Data Analyses," Biometrics, The International Biometric Society, vol. 60(2), pages 306-314, June.
    6. Mulugeta Gebregziabher & Bryan Langholz, 2010. "A Semiparametric Missing-Data-Induced Intensity Method for Missing Covariate Data in Individually Matched Case–Control Studies," Biometrics, The International Biometric Society, vol. 66(3), pages 845-854, September.
    7. Samiran Sinha & Bhramar Mukherjee & Malay Ghosh, 2004. "Bayesian Semiparametric Modeling for Matched Case–Control Studies with Multiple Disease States," Biometrics, The International Biometric Society, vol. 60(1), pages 41-49, March.
    8. Jinbo Chen & Carmen Rodriguez, 2007. "Conditional Likelihood Methods for Haplotype-Based Association Analysis Using Matched Case–Control Data," Biometrics, The International Biometric Society, vol. 63(4), pages 1099-1107, December.
    9. Militino, A.F. & Goicoa, T. & Ugarte, M.D., 2012. "Estimating the percentage of food expenditure in small areas using bias-corrected P-spline based estimators," Computational Statistics & Data Analysis, Elsevier, vol. 56(10), pages 2934-2948.
    10. Lauren Hund & Jarvis T. Chen & Nancy Krieger & Brent A. Coull, 2012. "A Geostatistical Approach to Large-Scale Disease Mapping with Temporal Misalignment," Biometrics, The International Biometric Society, vol. 68(3), pages 849-858, September.
    11. I-Feng Lin & Myunghee Cho Paik, 2001. "Matched Case—Control Data Analysis with Selection Bias," Biometrics, The International Biometric Society, vol. 57(4), pages 1106-1112, December.
    12. Ngo, Long & Wand, Matthew P., 2004. "Smoothing with Mixed Model Software," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 9(i01).
    13. Tong Wang & Cheng He & Fujie Jin & Yu Jeffrey Hu, 2022. "Evaluating the Effectiveness of Marketing Campaigns for Malls Using a Novel Interpretable Machine Learning Model," Information Systems Research, INFORMS, vol. 33(2), pages 659-677, June.
    14. Øystein Sørensen & Anders M. Fjell & Kristine B. Walhovd, 2023. "Longitudinal Modeling of Age-Dependent Latent Traits with Generalized Additive Latent and Mixed Models," Psychometrika, Springer;The Psychometric Society, vol. 88(2), pages 456-486, June.
    15. Roca-Pardinas, Javier & Cadarso-Suarez, Carmen & Tahoces, Pablo G. & Lado, Maria J., 2008. "Assessing continuous bivariate effects among different groups through nonparametric regression models: An application to breast cancer detection," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 1958-1970, January.
    16. Mariano J. Valderrama & Francisco A. Ocaña & Ana M. Aguilera & Francisco M. Ocaña-Peinado, 2010. "Forecasting Pollen Concentration by a Two-Step Functional Model," Biometrics, The International Biometric Society, vol. 66(2), pages 578-585, June.
    17. M. P. Wand, 2003. "Smoothing and mixed models," Computational Statistics, Springer, vol. 18(2), pages 223-249, July.
    18. Stremersch, S. & Lemmens, A., 2008. "Sales Growth of New Pharmaceuticals Across the Globe: The Role of Regulatory Regimes," ERIM Report Series Research in Management ERS-2008-026-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    19. repec:jss:jstsof:09:i01 is not listed on IDEAS
    20. Hua Yun Chen, 2007. "A Semiparametric Odds Ratio Model for Measuring Association," Biometrics, The International Biometric Society, vol. 63(2), pages 413-421, June.
    21. Michael Wegener & Göran Kauermann, 2008. "Examining heterogeneity in implied equity risk premium using penalized splines," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 92(1), pages 35-56, February.

    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:59:y:2003:i:4:p:1158-1169. 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.