Converging Science and Practice in Analyzing Evaluation Data

Abstract

A strategy is presented for converging science and practice which focuses on the needs of scientists and policymakers in analyzing evaluation data. Emphasis is placed on employing powerful statistical techniques that maximize the evaluators' confidence in their results. Attention is also drawn to the need for producing results which can be easily communicated to and interpreted by policymakers. In regard to these requirements, the discussion concerns application of four statistical techniques: factor analysis, Guttman scalogram analysis, multiple classification analysis and cross-break analysis. Each statistical analysis technique is described as to its value in evaluation research for dealing with problems known to inhibit the convergence of science and practice. The application of these techniques is demonstrated by illustrations taken from previous evaluation studies. The paper concludes with implications for stimulating the extent and quality of evaluation use.