IDEAS home Printed from https://ideas.repec.org/a/sae/medema/v35y2015i5p564-566.html
   My bibliography  Save this article

Value of Information

Author

Listed:
  • Nicky J. Welton
  • Howard H. Z. Thom

Abstract

No abstract is available for this item.

Suggested Citation

  • Nicky J. Welton & Howard H. Z. Thom, 2015. "Value of Information," Medical Decision Making, , vol. 35(5), pages 564-566, July.
    • Handle: RePEc:sae:medema:v:35:y:2015:i:5:p:564-566
    DOI: 10.1177/0272989X15579164
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0272989X15579164
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0272989X15579164?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. M. D. Stevenson & J. Oakley & J. B. Chilcott, 2004. "Gaussian Process Modeling in Conjunction with Individual Patient Simulation Modeling: A Case Study Describing the Calculation of Cost-Effectiveness Ratios for the Treatment of Established Osteoporosis," Medical Decision Making, , vol. 24(1), pages 89-100, January.
    2. Mark Strong & Jeremy E. Oakley & Jim Chilcott, 2012. "Managing structural uncertainty in health economic decision models: a discrepancy approach," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 61(1), pages 25-45, January.
    3. Christopher H. Jackson & Simon G. Thompson & Linda D. Sharples, 2009. "Accounting for uncertainty in health economic decision models by using model averaging," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(2), pages 383-404, April.
    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. Aditya Sai & Carolina Vivas-Valencia & Thomas F. Imperiale & Nan Kong, 2019. "Multiobjective Calibration of Disease Simulation Models Using Gaussian Processes," Medical Decision Making, , vol. 39(5), pages 540-552, July.
    2. Neil Hawkins & Mark Sculpher & David Epstein, 2005. "Cost-Effectiveness Analysis of Treatments for Chronic Disease: Using R to Incorporate Time Dependency of Treatment Response," Medical Decision Making, , vol. 25(5), pages 511-519, September.
    3. Abbygail Jaccard & Lise Retat & Martin Brown & Laura Webber & Zaid Chalabi, 2018. "Global Sensitivity Analysis of a Model Simulating an Individual’s Health State through Their Lifetime," International Journal of Microsimulation, International Microsimulation Association, vol. 11(3), pages 100-121.
    4. Andrija S Grustam & Nasuh Buyukkaramikli & Ron Koymans & Hubertus J M Vrijhoef & Johan L Severens, 2019. "Value of information analysis in telehealth for chronic heart failure management," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-23, June.
    5. Salah Ghabri & Irina Cleemput & Jean-Michel Josselin, 2018. "Towards a New Framework for Addressing Structural Uncertainty in Health Technology Assessment Guidelines," PharmacoEconomics, Springer, vol. 36(2), pages 127-130, February.
    6. Afschin Gandjour, 2010. "Investment in quality improvement: how to maximize the return," Health Economics, John Wiley & Sons, Ltd., vol. 19(1), pages 31-42, January.
    7. Mark Strong & Jeremy E. Oakley & Alan Brennan, 2014. "Estimating Multiparameter Partial Expected Value of Perfect Information from a Probabilistic Sensitivity Analysis Sample," Medical Decision Making, , vol. 34(3), pages 311-326, April.
    8. Bas Groot Koerkamp & Theo Stijnen & Milton C. Weinstein & M. G. Myriam Hunink, 2011. "The Combined Analysis of Uncertainty and Patient Heterogeneity in Medical Decision Models," Medical Decision Making, , vol. 31(4), pages 650-661, July.
    9. Christopher H. Jackson & Linda D. Sharples & Simon G. Thompson, 2010. "Structural and parameter uncertainty in Bayesian cost‐effectiveness models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 59(2), pages 233-253, March.
    10. Andrea Gabrio & Michael J. Daniels & Gianluca Baio, 2020. "A Bayesian parametric approach to handle missing longitudinal outcome data in trial‐based health economic evaluations," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(2), pages 607-629, February.
    11. Xing Liu & Enrico Zio & Emanuele Borgonovo & Elmar Plischke, 2024. "A Systematic Approach of Global Sensitivity Analysis and Its Application to a Model for the Quantification of Resilience of Interconnected Critical Infrastructures," Energies, MDPI, vol. 17(8), pages 1-24, April.
    12. Hyder, Kieran & Rossberg, Axel G. & Allen, J. Icarus & Austen, Melanie C. & Barciela, Rosa M. & Bannister, Hayley J. & Blackwell, Paul G. & Blanchard, Julia L. & Burrows, Michael T. & Defriez, Emma & , 2015. "Making modelling count - increasing the contribution of shelf-seas community and ecosystem models to policy development and management," Marine Policy, Elsevier, vol. 61(C), pages 291-302.
    13. Quang A. Le, 2016. "Structural Uncertainty of Markov Models for Advanced Breast Cancer," Medical Decision Making, , vol. 36(5), pages 629-640, July.
    14. Marta Soares & Luísa Canto e Castro, 2012. "Continuous Time Simulation and Discretized Models for Cost-Effectiveness Analysis," PharmacoEconomics, Springer, vol. 30(12), pages 1101-1117, December.
    15. Christopher H. Jackson & Laura Bojke & Simon G. Thompson & Karl Claxton & Linda D. Sharples, 2011. "A Framework for Addressing Structural Uncertainty in Decision Models," Medical Decision Making, , vol. 31(4), pages 662-674, July.
    16. Hawre Jalal & Bryan Dowd & François Sainfort & Karen M. Kuntz, 2013. "Linear Regression Metamodeling as a Tool to Summarize and Present Simulation Model Results," Medical Decision Making, , vol. 33(7), pages 880-890, October.
    17. Vanina Forget, 2012. "Doing well and doing good: a multi-dimensional puzzle," Working Papers hal-00672037, HAL.
    18. Marta O Soares & L Canto e Castro, 2010. "Simulation or cohort models? Continuous time simulation and discretized Markov models to estimate cost-effectiveness," Working Papers 056cherp, Centre for Health Economics, University of York.
    19. Marta O. Soares & Luísa Canto e Castro, 2012. "Continuous Time Simulation and Discretized Models for Cost-Effectiveness Analysis," PharmacoEconomics, Springer, vol. 30(12), pages 1101-1117, December.
    20. Anthony O'Hagan & Matt Stevenson & Jason Madan, 2007. "Monte Carlo probabilistic sensitivity analysis for patient level simulation models: efficient estimation of mean and variance using ANOVA," Health Economics, John Wiley & Sons, Ltd., vol. 16(10), pages 1009-1023.

    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:sae:medema:v:35:y:2015:i:5:p:564-566. 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: SAGE Publications (email available below). General contact details of provider: .

    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.