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Individual results may vary: Inequality-probability bounds for some health-outcome treatment effects

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  • Mullahy, John

Abstract

While many results from the treatment-effect and related literatures are familiar and have been applied productively in health economics evaluations, other potentially useful results from those literatures have had little influence on health economics practice. With the intent of demonstrating the value and use of some of these results in health economics applications, this paper focuses on one particular class of parameters that describe probabilities that one outcome is larger or smaller than other outcomes (“inequality probabilities”). While the properties of such parameters have been exposited in the technical literature, they have scarcely been considered in informing practical questions in health evaluations. This paper shows how such probabilities can be used informatively, and describes how they might be identified or bounded informatively given standard sampling assumptions and information only on marginal distributions of outcomes. The logic of these results and the empirical implementation thereof—sampling, estimation, and inference—are straightforward. Derivations are provided and several health-related applications are presented.

Suggested Citation

  • Mullahy, John, 2018. "Individual results may vary: Inequality-probability bounds for some health-outcome treatment effects," Journal of Health Economics, Elsevier, vol. 61(C), pages 151-162.
  • Handle: RePEc:eee:jhecon:v:61:y:2018:i:c:p:151-162
    DOI: 10.1016/j.jhealeco.2018.06.011
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    2. Bartalotti, Otávio & Kédagni, Désiré & Possebom, Vitor, 2023. "Identifying marginal treatment effects in the presence of sample selection," Journal of Econometrics, Elsevier, vol. 234(2), pages 565-584.
    3. John Mullahy, 2020. "Discovering Treatment Effectiveness via Median Treatment Effects—Applications to COVID-19 Clinical Trials," NBER Working Papers 27895, National Bureau of Economic Research, Inc.
    4. Zhehao Zhang & Thomas S. Richardson, 2024. "Bounds on the Distribution of a Sum of Two Random Variables: Revisiting a problem of Kolmogorov with application to Individual Treatment Effects," Papers 2405.08806, arXiv.org.
    5. Marx, Philip, 2024. "Sharp bounds in the latent index selection model," Journal of Econometrics, Elsevier, vol. 238(2).
    6. John Mullahy, 2018. "Treatment Effects with Multiple Outcomes," NBER Working Papers 25307, National Bureau of Economic Research, Inc.
    7. John Mullahy, 2021. "Discovering treatment effectiveness via median treatment effects—Applications to COVID‐19 clinical trials," Health Economics, John Wiley & Sons, Ltd., vol. 30(5), pages 1050-1069, May.
    8. Neil Christy & A. E. Kowalski, 2024. "Starting Small: Prioritizing Safety over Efficacy in Randomized Experiments Using the Exact Finite Sample Likelihood," Papers 2407.18206, arXiv.org.

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