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Bayesian Estimation of the Complier Average Casual Effect

Author

Listed:
  • van Hasselt, Martijn

    (University of North Carolina at Greensboro, Department of Economics)

  • Ferland, Timothy

    (University of North Carolina at Greensboro, Department of Economics)

  • Bray, Jeremy

    (University of North Carolina at Greensboro, Department of Economics)

  • Aldridge, Arnie

    (RTI International)

Abstract

We analyze two cases of randomized experiments with noncompliance. In the first case, individuals in the control group do not have access to the treatment and non- compliance only occurs in the treatment group. In the second case, which is com- mon in clinical studies, individuals in the control group are given a placebo. In this case, noncompliance occurs in both the treatment and control group. We present a Bayesian method-of-moments approach for estimating the complier average causal ef- fect (CACE). This procedure is valid under weak exclusion restrictions. This approach is contrasted with Gibbs sampling and data augmentation in a parametric model. The various procedures are evaluated in a simulation experiment and applied to clinical trial data from the COMBINE study.

Suggested Citation

  • van Hasselt, Martijn & Ferland, Timothy & Bray, Jeremy & Aldridge, Arnie, 2017. "Bayesian Estimation of the Complier Average Casual Effect," UNCG Economics Working Papers 17-14, University of North Carolina at Greensboro, Department of Economics.
    • Handle: RePEc:ris:uncgec:2017_014
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    References listed on IDEAS

    as
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    2. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-475, March.
    3. Chib, Siddhartha & Jacobi, Liana, 2008. "Analysis of treatment response data from eligibility designs," Journal of Econometrics, Elsevier, vol. 144(2), pages 465-478, June.
    4. Roderick J. Little & Qi Long & Xihong Lin, 2009. "A Comparison of Methods for Estimating the Causal Effect of a Treatment in Randomized Clinical Trials Subject to Noncompliance," Biometrics, The International Biometric Society, vol. 65(2), pages 640-649, June.
    5. Yahong Peng & Roderick J. A. Little & Trivellore E. Raghunathan, 2004. "An Extended General Location Model for Causal Inferences from Data Subject to Noncompliance and Missing Values," Biometrics, The International Biometric Society, vol. 60(3), pages 598-607, September.
    6. Chib, Siddhartha, 2007. "Analysis of treatment response data without the joint distribution of potential outcomes," Journal of Econometrics, Elsevier, vol. 140(2), pages 401-412, October.
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Noncompliance; casual effects; methods of moments; principal stratification;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation

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