Prevention Science

, Volume 11, Issue 3, pp 239–251 | Cite as

Investigating the Impact of Selection Bias in Dose-Response Analyses of Preventive Interventions

  • Herle M. McGowanEmail author
  • Robert L. Nix
  • Susan A. Murphy
  • Karen L. Bierman
  • Conduct Problems Prevention Research Group*


This paper focuses on the impact of selection bias in the context of extended, community-based prevention trials that attempt to “unpack” intervention effects and analyze mechanisms of change. Relying on dose-response analyses as the most general form of such efforts, this study provides two examples of how selection bias can affect the estimation of treatment effects. In Example 1, we describe an actual intervention in which selection bias was believed to influence the dose-response relation of an adaptive component in a preventive intervention for young children with severe behavior problems. In Example 2, we conduct a series of Monte Carlo simulations to illustrate just how severely selection bias can affect estimates in a dose-response analysis when the factors that affect dose are not recorded. We also assess the extent to which selection bias is ameliorated by the use of pretreatment covariates. We examine the implications of these examples and review trial design, data collection, and data analysis factors that can reduce selection bias in efforts to understand how preventive interventions have the effects they do.


Selection bias Preventive interventions Dose-response Simulations 


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Copyright information

© Society for Prevention Research 2010

Authors and Affiliations

  • Herle M. McGowan
    • 1
    Email author
  • Robert L. Nix
    • 2
  • Susan A. Murphy
    • 3
  • Karen L. Bierman
    • 2
  • Conduct Problems Prevention Research Group*
  1. 1.NCSU Department of StatisticsNorth Carolina State UniversityRaleighUSA
  2. 2.Pennsylvania State UniversityUniversity ParkUSA
  3. 3.University of MichiganAnn ArborUSA

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