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Adjusting for Attrition in School-Based Samples

Author

Listed:
  • K.A. McGuigan

    (RAND)

  • P.L. Ellickson

    (RAND)

  • R.D. Hays

    (RAND)

  • R.M. Bell

    (RAND)

Abstract

Attrition in longitudinal studies can introduce nonresponse bias when estimating parameters. Methods to correct for nonresponse include survey-based approaches (tracking) as well as analytically based methods (weighting, sample selection modeling). Using data from a multi- wave school-based study of adolescents, substance use estimates are compared across methods. Methods are validated by simulating effects of attrition at baseline, and the relative efficiency of each approach with respect to a known "gold standard" is calculated. Results indicate that weighting may provide sufficient adjustment for nonresponse in other, similar studies. Sample selection modeling requires assumptions that are not met in this setting, and severe bias results. The high costs associated with full tracking efforts may be avoidable, as here we find that tracking was an inefficient approach for bias reduction .

Suggested Citation

  • K.A. McGuigan & P.L. Ellickson & R.D. Hays & R.M. Bell, 1997. "Adjusting for Attrition in School-Based Samples," Evaluation Review, , vol. 21(5), pages 554-567, October.
    • Handle: RePEc:sae:evarev:v:21:y:1997:i:5:p:554-567
    DOI: 10.1177/0193841X9702100502
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    References listed on IDEAS

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    3. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    4. Pirie, P.L. & Murray, D.M. & Luepker, R.V., 1988. "Smoking prevalence in a cohort of adolescents, including absentees, dropouts, and transfers," American Journal of Public Health, American Public Health Association, vol. 78(2), pages 176-178.
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