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Causal inference from strip-plot designs in a potential outcomes framework

Author

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  • Alqallaf, Fatemah A.
  • Huda, S.
  • Mukerjee, Rahul

Abstract

A randomization-based theory of causal inference from strip-plot designs is developed. For any treatment contrast, we propose an unbiased estimator, work out its sampling variance, and obtain a conservative variance estimator which is shown to enjoy a minimaxity property.

Suggested Citation

  • Alqallaf, Fatemah A. & Huda, S. & Mukerjee, Rahul, 2019. "Causal inference from strip-plot designs in a potential outcomes framework," Statistics & Probability Letters, Elsevier, vol. 149(C), pages 55-62.
    • Handle: RePEc:eee:stapro:v:149:y:2019:i:c:p:55-62
    DOI: 10.1016/j.spl.2019.01.027
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    References listed on IDEAS

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    1. Tirthankar Dasgupta & Natesh S. Pillai & Donald B. Rubin, 2015. "Causal inference from 2-super-K factorial designs by using potential outcomes," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 77(4), pages 727-753, September.
    2. Rahul Mukerjee & Tirthankar Dasgupta & Donald B. Rubin, 2018. "Using Standard Tools From Finite Population Sampling to Improve Causal Inference for Complex Experiments," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(522), pages 868-881, April.
    3. Lu, Jiannan & Deng, Alex, 2017. "On randomization-based causal inference for matched-pair factorial designs," Statistics & Probability Letters, Elsevier, vol. 125(C), pages 99-103.
    4. Lu, Jiannan, 2016. "On randomization-based and regression-based inferences for 2K factorial designs," Statistics & Probability Letters, Elsevier, vol. 112(C), pages 72-78.
    5. Lu, Jiannan, 2016. "Covariate adjustment in randomization-based causal inference for 2K factorial designs," Statistics & Probability Letters, Elsevier, vol. 119(C), pages 11-20.
    6. Imbens,Guido W. & Rubin,Donald B., 2015. "Causal Inference for Statistics, Social, and Biomedical Sciences," Cambridge Books, Cambridge University Press, number 9780521885881, October.
    Full references (including those not matched with items on IDEAS)

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