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Random Measurement Error Does Not Bias the Treatment Effect Estimate in the Regression-Discontinuity Design

Author

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  • Joseph C. Cappelleri

    (Cornell University)

  • William M.K. Trochim

    (Cornell University)

  • T.D. Stanley

    (Hendrix College)

  • Charles S. Reichardt

    (Universcty of Denver)

Abstract

A recently published Evaluation Review article (April 1990) claimed that because of random measurement error in the pretest (and the regression toward the mean that results) the estimate of the treatment effect of the regression-discontinuity (RD) design is biased A conceptual approach and a set of computer simulations are presented to arrive at the opposite conclusion: random measurement error in the pretest does not bias the estimate of the treatment effect in the RD design. This article, the first of two dealing with measurement error in the RD design, concentrates specifically on the case of no interaction between pretest and treatment on posttest. The claim that the RD effect estimate is not biased due to measurement error is in full agreement with the conclusion reached by several authors who have examined the design over the last two decades.

Suggested Citation

  • Joseph C. Cappelleri & William M.K. Trochim & T.D. Stanley & Charles S. Reichardt, 1991. "Random Measurement Error Does Not Bias the Treatment Effect Estimate in the Regression-Discontinuity Design," Evaluation Review, , vol. 15(4), pages 395-419, August.
    • Handle: RePEc:sae:evarev:v:15:y:1991:i:4:p:395-419
    DOI: 10.1177/0193841X9101500401
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    References listed on IDEAS

    as
    1. Griliches, Zvi, 1974. "Errors in Variables and Other Unobservables," Econometrica, Econometric Society, vol. 42(6), pages 971-998, November.
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    Cited by:

    1. Lee Myoung-Jae, 2017. "Regression Discontinuity with Errors in the Running Variable: Effect on Truthful Margin," Journal of Econometric Methods, De Gruyter, vol. 6(1), pages 1-8, January.
    2. William M.K. Trochim & Joseph C. Cappelleri & Charles S. Reichardt, 1991. "Random Measurement Error Does Not Bias the Treatment Effect Estimate in the Regression-Discontinuity Design," Evaluation Review, , vol. 15(5), pages 571-604, October.
    3. Charles S. Reichardt & William M.K. Trochim & Joseph C. Cappelleri, 1995. "Reports of the Death of Regression-Discontinuity Analysis are Greatly Exaggerated," Evaluation Review, , vol. 19(1), pages 39-63, February.
    4. Joseph C. Cappelleri & Richard B. Darlington & William M.K. Trochim, 1994. "Power Analysis of Cutoff-Based Randomized Clinical Trials," Evaluation Review, , vol. 18(2), pages 141-152, April.
    5. T.D. Stanley, 1991. ""Regression-Discontinuity Design" By Any Other Name Might Be Less Problematic," Evaluation Review, , vol. 15(5), pages 605-624, October.
    6. Jin-young Choi & Myoung-jae Lee, 2017. "Regression discontinuity: review with extensions," Statistical Papers, Springer, vol. 58(4), pages 1217-1246, December.

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