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Exact confidence intervals in the presence of interference

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  • Rigdon, Joseph
  • Hudgens, Michael G.

Abstract

For two-stage randomized experiments assuming partial interference, exact confidence intervals are proposed for treatment effects on a binary outcome. Empirical studies demonstrate the new intervals have narrower width than previously proposed exact intervals based on the Hoeffding inequality.

Suggested Citation

  • Rigdon, Joseph & Hudgens, Michael G., 2015. "Exact confidence intervals in the presence of interference," Statistics & Probability Letters, Elsevier, vol. 105(C), pages 130-135.
  • Handle: RePEc:eee:stapro:v:105:y:2015:i:c:p:130-135
    DOI: 10.1016/j.spl.2015.06.011
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    References listed on IDEAS

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    1. Betsy Sinclair & Margaret McConnell & Donald P. Green, 2012. "Detecting Spillover Effects: Design and Analysis of Multilevel Experiments," American Journal of Political Science, John Wiley & Sons, vol. 56(4), pages 1055-1069, October.
    2. Hong, Guanglei & Raudenbush, Stephen W., 2006. "Evaluating Kindergarten Retention Policy: A Case Study of Causal Inference for Multilevel Observational Data," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 901-910, September.
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    4. Hudgens, Michael G. & Halloran, M. Elizabeth, 2008. "Toward Causal Inference With Interference," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 832-842, June.
    5. Rosenbaum, Paul R., 2007. "Interference Between Units in Randomized Experiments," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 191-200, March.
    6. Sobel, Michael E., 2006. "What Do Randomized Studies of Housing Mobility Demonstrate?: Causal Inference in the Face of Interference," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1398-1407, December.
    7. Lan Liu & Michael G. Hudgens, 2014. "Large Sample Randomization Inference of Causal Effects in the Presence of Interference," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(505), pages 288-301, March.
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    Cited by:

    1. Denis Fougère & Nicolas Jacquemet, 2020. "Policy Evaluation Using Causal Inference Methods," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-03455978, HAL.
    2. Gonzalo Vazquez-Bare, 2017. "Identification and Estimation of Spillover Effects in Randomized Experiments," Papers 1711.02745, arXiv.org, revised Jan 2022.
    3. Karlsson, Maria & Lundin, Mathias, 2016. "On statistical methods for labor market evaluation under interference between units," Working Paper Series 2016:24, IFAU - Institute for Evaluation of Labour Market and Education Policy.
    4. Jizhou Liu, 2023. "Inference for Two-stage Experiments under Covariate-Adaptive Randomization," Papers 2301.09016, arXiv.org, revised Oct 2024.

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