IDEAS home Printed from https://ideas.repec.org/a/wly/riskan/v35y2015i1p68-76.html
   My bibliography  Save this article

Simultaneous Inference for Model Averaging of Derived Parameters

Author

Listed:
  • Signe M. Jensen
  • Christian Ritz

Abstract

Model averaging is a useful approach for capturing uncertainty due to model selection. Currently, this uncertainty is often quantified by means of approximations that do not easily extend to simultaneous inference. Moreover, in practice there is a need for both model averaging and simultaneous inference for derived parameters calculated in an after‐fitting step. We propose a method for obtaining asymptotically correct standard errors for one or several model‐averaged estimates of derived parameters and for obtaining simultaneous confidence intervals that asymptotically control the family‐wise Type I error rate. The performance of the method in terms of coverage is evaluated using a simulation study and the applicability of the method is demonstrated by means of three concrete examples.

Suggested Citation

  • Signe M. Jensen & Christian Ritz, 2015. "Simultaneous Inference for Model Averaging of Derived Parameters," Risk Analysis, John Wiley & Sons, vol. 35(1), pages 68-76, January.
  • Handle: RePEc:wly:riskan:v:35:y:2015:i:1:p:68-76
    DOI: 10.1111/risa.12242
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/risa.12242
    Download Restriction: no

    File URL: https://libkey.io/10.1111/risa.12242?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. Sarah C. Taft & Stephanie A. Hines, 2012. "Benchmark Dose Analysis for Bacillus anthracis Inhalation Exposures in the Nonhuman Primate," Risk Analysis, John Wiley & Sons, vol. 32(10), pages 1750-1768, October.
    2. Kan Shao & Jeffrey S. Gift, 2014. "Model Uncertainty and Bayesian Model Averaged Benchmark Dose Estimation for Continuous Data," Risk Analysis, John Wiley & Sons, vol. 34(1), pages 101-120, January.
    3. Hojin Moon & Steven B. Kim & James J. Chen & Nysia I. George & Ralph L. Kodell, 2013. "Model Uncertainty and Model Averaging in the Estimation of Infectious Doses for Microbial Pathogens," Risk Analysis, John Wiley & Sons, vol. 33(2), pages 220-231, February.
    4. A. John Bailer & Robert B. Noble & Matthew W. Wheeler, 2005. "Model Uncertainty and Risk Estimation for Experimental Studies of Quantal Responses," Risk Analysis, John Wiley & Sons, vol. 25(2), pages 291-299, April.
    5. Ritz, Christian & Streibig, Jens C., 2005. "Bioassay Analysis Using R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 12(i05).
    6. Lelys Bravo Guenni & Susan J. Simmons & R. Webster West & Walter W. Piegorsch & Edsel A. Peña & Lingling An & Wensong Wu & Alissa A. Wickens & Hui Xiong & Wenhai Chen, 2012. "The impact of model uncertainty on benchmark dose estimation," Environmetrics, John Wiley & Sons, Ltd., vol. 23(8), pages 706-716, December.
    7. Christel Faes & Marc Aerts & Helena Geys & Geert Molenberghs, 2007. "Model Averaging Using Fractional Polynomials to Estimate a Safe Level of Exposure," Risk Analysis, John Wiley & Sons, vol. 27(1), pages 111-123, February.
    8. Daniela K. Nitcheva & Walter W. Piegorsch & R. Webster West & Ralph L. Kodell, 2005. "Multiplicity-Adjusted Inferences in Risk Assessment: Benchmark Analysis with Quantal Response Data," Biometrics, The International Biometric Society, vol. 61(1), pages 277-286, March.
    9. Christian Bressen Pipper & Christian Ritz & Hans Bisgaard, 2012. "A versatile method for confirmatory evaluation of the effects of a covariate in multiple models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 61(2), pages 315-326, March.
    10. Esben Budtz-Jørgensen & Niels Keiding & Philippe Grandjean, 2001. "Benchmark Dose Calculation from Epidemiological Data," Biometrics, The International Biometric Society, vol. 57(3), pages 698-706, September.
    11. Walter W. Piegorsch & R. Webster West, 2005. "Benchmark Analysis: Shopping with Proper Confidence," Risk Analysis, John Wiley & Sons, vol. 25(4), pages 913-920, August.
    12. Steven B. Kim & Ralph L. Kodell & Hojin Moon, 2014. "A Diversity Index for Model Space Selection in the Estimation of Benchmark and Infectious Doses via Model Averaging," Risk Analysis, John Wiley & Sons, vol. 34(3), pages 453-464, March.
    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. Signe M Jensen & Hanne Hauger & Christian Ritz, 2018. "Mediation analysis for logistic regression with interactions: Application of a surrogate marker in ophthalmology," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-7, February.
    2. Frank Schaarschmidt & Christian Ritz & Ludwig A. Hothorn, 2022. "The Tukey trend test: Multiplicity adjustment using multiple marginal models," Biometrics, The International Biometric Society, vol. 78(2), pages 789-797, June.
    3. Signe M. Jensen & Felix M. Kluxen & Christian Ritz, 2019. "A Review of Recent Advances in Benchmark Dose Methodology," Risk Analysis, John Wiley & Sons, vol. 39(10), pages 2295-2315, October.
    4. Florent Baty & Christian Ritz & Signe Marie Jensen & Lukas Kern & Michael Tamm & Martin Hugo Brutsche, 2017. "Multimodel inference applied to oxygen recovery kinetics after 6-min walk tests in patients with chronic obstructive pulmonary disease," PLOS ONE, Public Library of Science, vol. 12(11), pages 1-12, November.

    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. Signe M. Jensen & Felix M. Kluxen & Christian Ritz, 2019. "A Review of Recent Advances in Benchmark Dose Methodology," Risk Analysis, John Wiley & Sons, vol. 39(10), pages 2295-2315, October.
    2. Walter W. Piegorsch & Hui Xiong & Rabi N. Bhattacharya & Lizhen Lin, 2014. "Benchmark Dose Analysis via Nonparametric Regression Modeling," Risk Analysis, John Wiley & Sons, vol. 34(1), pages 135-151, January.
    3. Edsel A. Peña & Wensong Wu & Walter Piegorsch & Ronald W. West & LingLing An, 2017. "Model Selection and Estimation with Quantal‐Response Data in Benchmark Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 37(4), pages 716-732, April.
    4. Matthew W. Wheeler & Todd Blessinger & Kan Shao & Bruce C. Allen & Louis Olszyk & J. Allen Davis & Jeffrey S Gift, 2020. "Quantitative Risk Assessment: Developing a Bayesian Approach to Dichotomous Dose–Response Uncertainty," Risk Analysis, John Wiley & Sons, vol. 40(9), pages 1706-1722, September.
    5. Marc Aerts & Matthew W. Wheeler & José Cortiñas Abrahantes, 2020. "An extended and unified modeling framework for benchmark dose estimation for both continuous and binary data," Environmetrics, John Wiley & Sons, Ltd., vol. 31(7), November.
    6. Walter W. Piegorsch & Susan L. Cutter & Frank Hardisty, 2007. "Benchmark Analysis for Quantifying Urban Vulnerability to Terrorist Incidents," Risk Analysis, John Wiley & Sons, vol. 27(6), pages 1411-1425, December.
    7. Robert B. Noble & A. John Bailer & Robert Park, 2009. "Model‐Averaged Benchmark Concentration Estimates for Continuous Response Data Arising from Epidemiological Studies," Risk Analysis, John Wiley & Sons, vol. 29(4), pages 558-564, April.
    8. Walter W. Piegorsch, 2010. "Translational benchmark risk analysis," Journal of Risk Research, Taylor & Francis Journals, vol. 13(5), pages 653-667, July.
    9. Steven B. Kim & Ralph L. Kodell & Hojin Moon, 2014. "A Diversity Index for Model Space Selection in the Estimation of Benchmark and Infectious Doses via Model Averaging," Risk Analysis, John Wiley & Sons, vol. 34(3), pages 453-464, March.
    10. Matthew W. Wheeler & Jose Cortiñas Abrahantes & Marc Aerts & Jeffery S. Gift & Jerry Allen Davis, 2022. "Continuous model averaging for benchmark dose analysis: Averaging over distributional forms," Environmetrics, John Wiley & Sons, Ltd., vol. 33(5), August.
    11. Hojin Moon & Steven B. Kim & James J. Chen & Nysia I. George & Ralph L. Kodell, 2013. "Model Uncertainty and Model Averaging in the Estimation of Infectious Doses for Microbial Pathogens," Risk Analysis, John Wiley & Sons, vol. 33(2), pages 220-231, February.
    12. Kan Shao & Jeffrey S. Gift, 2014. "Model Uncertainty and Bayesian Model Averaged Benchmark Dose Estimation for Continuous Data," Risk Analysis, John Wiley & Sons, vol. 34(1), pages 101-120, January.
    13. Jin‐Hua Chen & Chun‐Shu Chen & Meng‐Fan Huang & Hung‐Chih Lin, 2016. "Estimating the Probability of Rare Events Occurring Using a Local Model Averaging," Risk Analysis, John Wiley & Sons, vol. 36(10), pages 1855-1870, October.
    14. Floriane Larras & Agnès Bouchez & Frédéric Rimet & Bernard Montuelle, 2012. "Using Bioassays and Species Sensitivity Distributions to Assess Herbicide Toxicity towards Benthic Diatoms," PLOS ONE, Public Library of Science, vol. 7(8), pages 1-9, August.
    15. Esben Budtz‐Jørgensen & David Bellinger & Bruce Lanphear & Philippe Grandjean & on behalf of the International Pooled Lead Study Investigators, 2013. "An International Pooled Analysis for Obtaining a Benchmark Dose for Environmental Lead Exposure in Children," Risk Analysis, John Wiley & Sons, vol. 33(3), pages 450-461, March.
    16. Kan Shao & Mitchell J. Small, 2011. "Potential Uncertainty Reduction in Model‐Averaged Benchmark Dose Estimates Informed by an Additional Dose Study," Risk Analysis, John Wiley & Sons, vol. 31(10), pages 1561-1575, October.
    17. Euro Pannacci & Daniele Del Buono & Maria Luce Bartucca & Luigi Nasini & Primo Proietti & Francesco Tei, 2020. "Herbicide Uptake and Regrowth Ability of Tall Fescue and Orchardgrass in S-Metolachlor-Contaminated Leachates from Sand Pot Experiment," Agriculture, MDPI, vol. 10(10), pages 1-10, October.
    18. Brice Ozenne & Esben Budtz-Jørgensen & Sebastian Elgaard Ebert, 2023. "Controlling the familywise error rate when performing multiple comparisons in a linear latent variable model," Computational Statistics, Springer, vol. 38(1), pages 1-23, March.
    19. Kahm, Matthias & Hasenbrink, Guido & Lichtenberg-Fraté, Hella & Ludwig, Jost & Kschischo, Maik, 2010. "grofit: Fitting Biological Growth Curves with R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 33(i07).
    20. Hector Sanz & John J Aponte & Jaroslaw Harezlak & Yan Dong & Aintzane Ayestaran & Augusto Nhabomba & Maxmillian Mpina & Obiang Régis Maurin & Núria Díez-Padrisa & Ruth Aguilar & Gemma Moncunill & Agna, 2017. "drLumi: An open-source package to manage data, calibrate, and conduct quality control of multiplex bead-based immunoassays data analysis," PLOS ONE, Public Library of Science, vol. 12(11), pages 1-18, November.

    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:wly:riskan:v:35:y:2015:i:1:p:68-76. 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://doi.org/10.1111/(ISSN)1539-6924 .

    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.