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Using Omitted Variable Bias to Assess Uncertainty in the Estimation of an AIDS Education Treatment Effect

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  • Sue M. Marcus

Abstract

In a comparison of a treatment group and a control group, a difference in results can correspond to the effect of the treatment; however, the difference might also be, at least in part, a reflection of pretreatment differences between the two populations. Covariance adjustment can reduce bias in the estimate of the treatment effect ( Cochran & Rubin, 1973 ); however, baseline group differences with respect to unobserved covariates which cannot be controlled can lead to hidden bias. This article presents a simple method which uses omitted variable bias to assess the uncertainty of the hidden bias by describing what scenarios regarding the unobserved covariate can lead to a given level of hidden bias. A comparison of a culturally sensitive AIDS video education program and a standard AIDS video education program is used as an illustration.

Suggested Citation

  • Sue M. Marcus, 1997. "Using Omitted Variable Bias to Assess Uncertainty in the Estimation of an AIDS Education Treatment Effect," Journal of Educational and Behavioral Statistics, , vol. 22(2), pages 193-201, June.
    • Handle: RePEc:sae:jedbes:v:22:y:1997:i:2:p:193-201
    DOI: 10.3102/10769986022002193
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    Cited by:

    1. Paul R. Rosenbaum, 2013. "Impact of Multiple Matched Controls on Design Sensitivity in Observational Studies," Biometrics, The International Biometric Society, vol. 69(1), pages 118-127, March.
    2. Paul R. Rosenbaum, 2011. "A New u-Statistic with Superior Design Sensitivity in Matched Observational Studies," Biometrics, The International Biometric Society, vol. 67(3), pages 1017-1027, September.
    3. Jesse Y. Hsu & Dylan S. Small, 2013. "Calibrating Sensitivity Analyses to Observed Covariates in Observational Studies," Biometrics, The International Biometric Society, vol. 69(4), pages 803-811, December.
    4. Ben B. Hansen & Paul R. Rosenbaum & Dylan S. Small, 2014. "Clustered Treatment Assignments and Sensitivity to Unmeasured Biases in Observational Studies," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(505), pages 133-144, March.

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