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Establishing Benchmarks for Outcome Indicators

Author

Listed:
  • Gary T. Henry

    (Georgia State University)

  • Matthew J. McTaggart

    (University of Akron)

  • James H. McMillan

    (Virginia Commonwealth University)

Abstract

Indicators of program performance are used as evaluative measures in a variety of fields. A particularly vexing problem for evaluation is the development of empirically based performance expectations. Should program sponsors be satisfied with average performance? How should evaluators account for client differences? This article presents a statistical technique for developing performance standards based on benchmark groups. The benchmark groups are selected using a multivariate technique that relies on a squared Euclidean distance method. For each observation unit, in this case a school district, a unique comparison group is selected. The performance of the district is compared to the performance of its benchmark group. Then the credibility, predictability, and equity of the method are tested. The approach meets or exceeds these test criteria and appears to be a viable, albeit controversial, approach for developing comparative performance standards.

Suggested Citation

  • Gary T. Henry & Matthew J. McTaggart & James H. McMillan, 1992. "Establishing Benchmarks for Outcome Indicators," Evaluation Review, , vol. 16(2), pages 131-150, April.
    • Handle: RePEc:sae:evarev:v:16:y:1992:i:2:p:131-150
    DOI: 10.1177/0193841X9201600202
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    References listed on IDEAS

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    1. I. T. Jolliffe, 1972. "Discarding Variables in a Principal Component Analysis. I: Artificial Data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 21(2), pages 160-173, June.
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    Cited by:

    1. Cook, Thomas J. & Vansant, Jerry & Stewart, Leslie & Adrian, Jamie, 1995. "Performance measurement: Lessons learned for development management," World Development, Elsevier, vol. 23(8), pages 1303-1315, August.

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