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Optimal Design and Purposeful Sampling: Complementary Methodologies for Implementation Research

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Abstract

Optimal design has been an under-utilized methodology. However, it has significant real-world applications, particularly in mixed methods implementation research. We review the concept and demonstrate how it can be used to assess the sensitivity of design decisions and balance competing needs. For observational studies, this methodology enables selection of the most informative study units. For experimental studies, it entails selecting and assigning study units to intervention conditions in the most informative manner. We blend optimal design methods with purposeful sampling to show how these two concepts balance competing needs when there are multiple study aims, a common situation in implementation research.

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Acknowledgments

Drs. Duan, Hoagwood, and Palinkas were funded through a Grant from the National Institute of Mental Health (P30-MH090322:K. Hoagwood, PI). The authors appreciate helpful comments from two anonymous reviewers.

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Authors and Affiliations

  1. Division of Biostatistics, Department of Psychiatry, Columbia University, 722 West 168th Street, R206, New York, NY, 10032, USA

    Naihua Duan

  2. Division of Epidemiology and Biostatistics, University of Illinois at Chicago, Chicago, IL, USA

    Dulal K. Bhaumik

  3. School of Social Work, University of Southern California, Los Angeles, CA, USA

    Lawrence A. Palinkas

  4. Department of Child and Adolescent Psychiatry, New York University, New York, NY, USA

    Kimberly Hoagwood

Authors
  1. Naihua Duan
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  2. Dulal K. Bhaumik
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  3. Lawrence A. Palinkas
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  4. Kimberly Hoagwood
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Correspondence to Naihua Duan.

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Duan, N., Bhaumik, D.K., Palinkas, L.A. et al. Optimal Design and Purposeful Sampling: Complementary Methodologies for Implementation Research. Adm Policy Ment Health 42, 524–532 (2015). https://doi.org/10.1007/s10488-014-0596-7

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  • DOI: https://doi.org/10.1007/s10488-014-0596-7

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