IDEAS home Printed from https://ideas.repec.org/a/sae/medema/v29y2009i1p140-148.html
   My bibliography  Save this article

Improving Fast and Frugal Modeling in Relation to Regression Analysis: Test of 3 Models for Medical Decision Making

Author

Listed:
  • Lars G. Backlund

    (Center for Family and Community Medicine, Karolinska Institutet, Huddinge, Sweden)

  • Johan Bring

    (Center for Family and Community Medicine, Karolinska Institutet, Huddinge, Sweden)

  • Ylva SkÃ¥nér

    (Center for Family and Community Medicine, Karolinska Institutet, Huddinge, Sweden)

  • Lars-Erik Strender

    (Center for Family and Community Medicine, Karolinska Institutet, Huddinge, Sweden)

  • Henry Montgomery

    (Center for Family and Community Medicine, Karolinska Institutet, Huddinge, Sweden)

Abstract

Background . A matching heuristic (MH) model of decision making has been evaluated previously in a series of studies on medical decision making. The authors' purpose is to evaluate an extended MH model that considers the prevalence of cue values. Methods . Data from 2 previous studies were reanalyzed, one on judgments regarding drug treatment of hyperlipidemia and the other on diagnosing heart failure. The original MH model and the extended MH model were compared with logistic regression (LR) in terms of fit to actual judgments, number of cues, and the extent to which the cues were consistent with clinical guidelines. Results . There was a slightly better fit with LR compared with MH. The extended MH model gave a significantly better fit than the original MH model in the drug treatment task. In the diagnostic task, the number of cues was significantly lower in the MH models compared to LR, whereas in the therapeutic task, LR could be less or more frugal than the matching heuristic models depending on the significance level chosen for inclusion of cues. For the original MH model, but not for the extended MH model or LR, the most important cues in the drug treatment task were often used in a direction contrary to treatment guidelines. Conclusions . The extended MH model represents an improvement in that prevalence of cue values is adequately taken into account, which in turn may result in better fit and in better agreement with medical guidelines in the evaluation of cues.

Suggested Citation

  • Lars G. Backlund & Johan Bring & Ylva SkÃ¥nér & Lars-Erik Strender & Henry Montgomery, 2009. "Improving Fast and Frugal Modeling in Relation to Regression Analysis: Test of 3 Models for Medical Decision Making," Medical Decision Making, , vol. 29(1), pages 140-148, January.
    • Handle: RePEc:sae:medema:v:29:y:2009:i:1:p:140-148
    DOI: 10.1177/0272989X08326091
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0272989X08326091
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0272989X08326091?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. Gerd Gigerenzer & Reinhard Selten (ed.), 2002. "Bounded Rationality: The Adaptive Toolbox," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262571641, April.
    2. Backlund, Lars & Skaner, Ylva & Montgomery, Henry & Bring, Johan & Strender, Lars-Erik, 2003. "Doctors' decision processes in a drug-prescription task: The validity of rating scales and think-aloud reports," Organizational Behavior and Human Decision Processes, Elsevier, vol. 91(1), pages 108-117, May.
    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. Aspasia Tsaoussi & Eleni Zervogianni, 2010. "Judges as satisficers: a law and economics perspective on judicial liability," European Journal of Law and Economics, Springer, vol. 29(3), pages 333-357, June.
    2. Nicolas Marciales Parra, 2013. "A mathematical model for consumers based on aspiration adaptation theory and bounded rationality," Review of Applied Socio-Economic Research, Pro Global Science Association, vol. 5(1), pages 136-143, June.
    3. Binder, Carola C., 2017. "Measuring uncertainty based on rounding: New method and application to inflation expectations," Journal of Monetary Economics, Elsevier, vol. 90(C), pages 1-12.
    4. Giovanni Dosi & Marcelo C. Pereira & Maria Enrica Virgillito, 2017. "The footprint of evolutionary processes of learning and selection upon the statistical properties of industrial dynamics," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 26(2), pages 187-210.
    5. Filippini, Massimo & Hirl, Bettina & Masiero, Giuliano, 2018. "Habits and rational behaviour in residential electricity demand," Resource and Energy Economics, Elsevier, vol. 52(C), pages 137-152.
    6. Pennings, Clint L.P. & van Dalen, Jan & Rook, Laurens, 2019. "Coordinating judgmental forecasting: Coping with intentional biases," Omega, Elsevier, vol. 87(C), pages 46-56.
    7. Giovanni Dosi & Mauro Napoletano & Andrea Roventini & Joseph E. Stiglitz & Tania Treibich, 2020. "Rational Heuristics? Expectations And Behaviors In Evolving Economies With Heterogeneous Interacting Agents," Economic Inquiry, Western Economic Association International, vol. 58(3), pages 1487-1516, July.
    8. Duersch, Peter & Oechssler, Jörg & Schipper, Burkhard C., 2012. "Unbeatable imitation," Games and Economic Behavior, Elsevier, vol. 76(1), pages 88-96.
    9. Ann-Kathrin Koessler & Stefanie Engel, 2021. "Policies as Information Carriers: How Environmental Policies May Change Beliefs and Consequent Behavior," International Review of Environmental and Resource Economics, now publishers, vol. 15(1-2), pages 1-31, July.
    10. Joeri Schasfoort & Antoine Godin & Dirk Bezemer & Alessandro Caiani & Stephen Kinsella, 2017. "Monetary Policy Transmission In A Macroeconomic Agent-Based Model," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 20(08), pages 1-35, December.
    11. Spiliopoulos, Leonidas, 2013. "Beyond fictitious play beliefs: Incorporating pattern recognition and similarity matching," Games and Economic Behavior, Elsevier, vol. 81(C), pages 69-85.
    12. Ooi, Chai-Aun & Hooy, Chee-Wooi, 2022. "Muslim CEOs, risk-taking and firm performance," Pacific-Basin Finance Journal, Elsevier, vol. 74(C).
    13. Robinson, Scott A. & Rai, Varun, 2015. "Determinants of spatio-temporal patterns of energy technology adoption: An agent-based modeling approach," Applied Energy, Elsevier, vol. 151(C), pages 273-284.
    14. David Ettinger & Philippe Jehiel, 2004. "Towards a Theory of Deception," Levine's Bibliography 122247000000000247, UCLA Department of Economics.
    15. Annicchiarico, Barbara & Di Dio, Fabio & Diluiso, Francesca, 2024. "Climate actions, market beliefs, and monetary policy," Journal of Economic Behavior & Organization, Elsevier, vol. 218(C), pages 176-208.
    16. Cheng, Ing-Haw & Hsiaw, Alice, 2022. "Distrust in experts and the origins of disagreement," Journal of Economic Theory, Elsevier, vol. 200(C).
    17. Alexander Sohn, 2015. "Beyond Conventional Wage Discrimination Analysis: Assessing Comprehensive Wage Distributions of Males and Females Using Structured Additive Distributional Regression," SOEPpapers on Multidisciplinary Panel Data Research 802, DIW Berlin, The German Socio-Economic Panel (SOEP).
    18. Di Caprio, Debora & Santos-Arteaga, Francisco J. & Tavana, Madjid, 2019. "The role of anticipated emotions and the value of information in determining sequential search incentives," Operations Research Perspectives, Elsevier, vol. 6(C).
    19. Dal Forno, Arianna & Merlone, Ugo, 2010. "Effort dynamics in supervised work groups," Journal of Economic Behavior & Organization, Elsevier, vol. 75(3), pages 413-425, September.
    20. Mihály Ormos & Dusán Timotity, 2017. "Expected downside risk and asset prices: characteristics of emerging and developed European markets," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 44(3), pages 529-546, August.

    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:29:y:2009:i:1:p:140-148. 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.