IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v57y2001i2p539-545.html
   My bibliography  Save this article

Simple Incorporation of Interactions into Additive Models

Author

Listed:
  • Brent A. Coull
  • David Ruppert
  • M. P. Wand

Abstract

No abstract is available for this item.

Suggested Citation

  • 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.
  • Handle: RePEc:bla:biomet:v:57:y:2001:i:2:p:539-545
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/j.0006-341X.2001.00539.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. J. G. Booth & J. P. Hobert, 1999. "Maximizing generalized linear mixed model likelihoods with an automated Monte Carlo EM algorithm," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(1), pages 265-285.
    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. de Uña Álvarez, Jacobo & Roca Pardiñas, Javier, 2009. "Additive models in censored regression," Computational Statistics & Data Analysis, Elsevier, vol. 53(9), pages 3490-3501, July.
    2. Ugarte, M.D. & Goicoa, T. & Militino, A.F. & Durbán, M., 2009. "Spline smoothing in small area trend estimation and forecasting," Computational Statistics & Data Analysis, Elsevier, vol. 53(10), pages 3616-3629, August.
    3. Veerabhadran Baladandayuthapani & Bani K. Mallick & Mee Young Hong & Joanne R. Lupton & Nancy D. Turner & Raymond J. Carroll, 2008. "Bayesian Hierarchical Spatially Correlated Functional Data Analysis with Application to Colon Carcinogenesis," Biometrics, The International Biometric Society, vol. 64(1), pages 64-73, March.
    4. J. D. Opsomer & G. Claeskens & M. G. Ranalli & G. Kauermann & F. J. Breidt, 2008. "Non‐parametric small area estimation using penalized spline regression," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(1), pages 265-286, February.
    5. repec:jss:jstsof:09:i01 is not listed on IDEAS
    6. O. Gimenez & C. Crainiceanu & C. Barbraud & S. Jenouvrier & B. J. T. Morgan, 2006. "Semiparametric Regression in Capture–Recapture Modeling," Biometrics, The International Biometric Society, vol. 62(3), pages 691-698, September.
    7. 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.
    8. 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.
    9. Stefan Stremersch & Aurélie Lemmens, 2009. "Sales Growth of New Pharmaceuticals Across the Globe: The Role of Regulatory Regimes," Marketing Science, INFORMS, vol. 28(4), pages 690-708, 07-08.
    10. Maria Durbán & Iain D. Currie, 2003. "A note on P-spline additive models with correlated errors," Computational Statistics, Springer, vol. 18(2), pages 251-262, July.
    11. 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.
    12. 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.
    13. Wunder, Christoph & Schwarze, Johannes, 2009. "Is Posner Right? An Empirical Test of the Posner Argument for Transferring Health Spending from Old Women to Old Men," IZA Discussion Papers 4485, Institute of Labor Economics (IZA).
    14. Ngo, Long & Wand, Matthew P., 2004. "Smoothing with Mixed Model Software," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 9(i01).
    15. 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.
    16. 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.
    17. 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.
    18. M. P. Wand, 2003. "Smoothing and mixed models," Computational Statistics, Springer, vol. 18(2), pages 223-249, July.
    19. 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.
    20. Al Kadiri, M. & Carroll, R.J. & Wand, M.P., 2010. "Marginal longitudinal semiparametric regression via penalized splines," Statistics & Probability Letters, Elsevier, vol. 80(15-16), pages 1242-1252, August.
    21. 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.

    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. Shu Yang & Jae Kwang Kim, 2016. "Likelihood-based Inference with Missing Data Under Missing-at-Random," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(2), pages 436-454, June.
    2. Hemant Kulkarni & Jayabrata Biswas & Kiranmoy Das, 2019. "A joint quantile regression model for multiple longitudinal outcomes," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 103(4), pages 453-473, December.
    3. Tatiyana V. Apanasovich & David Ruppert & Joanne R. Lupton & Natasa Popovic & Nancy D. Turner & Robert S. Chapkin & Raymond J. Carroll, 2008. "Aberrant Crypt Foci and Semiparametric Modeling of Correlated Binary Data," Biometrics, The International Biometric Society, vol. 64(2), pages 490-500, June.
    4. Ricardo Smith Ramírez, 2007. "FIML estimation of treatment effect models with endogenous selection and multiple censored responses via a Monte Carlo EM Algorithm," Working papers DTE 403, CIDE, División de Economía.
    5. Brent A. Coull & Alan Agresti, 2000. "Random Effects Modeling of Multiple Binomial Responses Using the Multivariate Binomial Logit-Normal Distribution," Biometrics, The International Biometric Society, vol. 56(1), pages 73-80, March.
    6. J. E. Mills & C. A. Field & D. J. Dupuis, 2002. "Marginally Specified Generalized Linear Mixed Models: A Robust Approach," Biometrics, The International Biometric Society, vol. 58(4), pages 727-734, December.
    7. Jan Pablo Burgard & Patricia Dörr & Ralf Münnich, 2020. "Monte-Carlo Simulation Studies in Survey Statistics – An Appraisal," Research Papers in Economics 2020-04, University of Trier, Department of Economics.
    8. Kauermann, Goran & Xu, Ronghui & Vaida, Florin, 2008. "Stacked Laplace-EM algorithm for duration models with time-varying and random effects," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2514-2528, January.
    9. Steffen Nestler & Sarah Humberg, 2022. "A Lasso and a Regression Tree Mixed-Effect Model with Random Effects for the Level, the Residual Variance, and the Autocorrelation," Psychometrika, Springer;The Psychometric Society, vol. 87(2), pages 506-532, June.
    10. Koutchade, Philippe & Carpentier, Alain & Féménia, Fabienne, 2015. "Empirical modeling of production decisions of heterogeneous farmers with random parameter models," Working Papers 210097, Institut National de la recherche Agronomique (INRA), Departement Sciences Sociales, Agriculture et Alimentation, Espace et Environnement (SAE2).
    11. Maria Marino & Alessio Farcomeni, 2015. "Linear quantile regression models for longitudinal experiments: an overview," METRON, Springer;Sapienza Università di Roma, vol. 73(2), pages 229-247, August.
    12. Gonzalez, Jorge & Tuerlinckx, Francis & De Boeck, Paul & Cools, Ronald, 2006. "Numerical integration in logistic-normal models," Computational Statistics & Data Analysis, Elsevier, vol. 51(3), pages 1535-1548, December.
    13. Patricia Dörr & Jan Pablo Burgard, 2019. "Data-driven transformations and survey-weighting for linear mixed models," Research Papers in Economics 2019-16, University of Trier, Department of Economics.
    14. An, Xinming & Bentler, Peter M., 2012. "Efficient direct sampling MCEM algorithm for latent variable models with binary responses," Computational Statistics & Data Analysis, Elsevier, vol. 56(2), pages 231-244.
    15. Hongbin Zhang & Lang Wu, 2018. "A non‐linear model for censored and mismeasured time varying covariates in survival models, with applications in human immunodeficiency virus and acquired immune deficiency syndrome studies," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(5), pages 1437-1450, November.
    16. Ren, Dianxu & Stone, Roslyn A., 2007. "A Bayesian approach for analyzing a cluster-randomized trial with adjustment for risk misclassification," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 5507-5518, August.
    17. Emily M. Mitchell & Robert H. Lyles & Amita K. Manatunga & Michelle Danaher & Neil J. Perkins & Enrique F. Schisterman, 2014. "Regression for skewed biomarker outcomes subject to pooling," Biometrics, The International Biometric Society, vol. 70(1), pages 202-211, March.
    18. Angelo Moretti, 2023. "Estimation of small area proportions under a bivariate logistic mixed model," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(4), pages 3663-3684, August.
    19. Baghishani, Hossein & Mohammadzadeh, Mohsen, 2011. "A data cloning algorithm for computing maximum likelihood estimates in spatial generalized linear mixed models," Computational Statistics & Data Analysis, Elsevier, vol. 55(4), pages 1748-1759, April.
    20. Fan, Chunpeng & Zhang, Donghui, 2014. "Wald-type rank tests: A GEE approach," Computational Statistics & Data Analysis, Elsevier, vol. 74(C), pages 1-16.

    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:57:y:2001:i:2:p:539-545. 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.