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This document explains how to analyze Extension program impacts using multivariate statistical techniques. It outlines phases of data analysis, including identifying data errors, assessing changes in impact indicators, and examining relationships between program participation and outcomes. The paper emphasizes the role of contextual variables in clarifying or distorting program effects and introduces concepts such as spurious, conditional, distorter, and suppressor relationships. By incorporating these variables, evaluators can avoid misleading conclusions and improve the validity of their findings. Publication date: September 1992.
References
Israel, Glenn D. 2015. Phases of Data Analysis. (PEOD-1). Gainesville: University of Florida, Institute of Agricultural Sciences.
Patton, Michael Quinn. 1982. Practical Evaluation. Beverly Hills, CA: Sage Publications
Rosenberg, Morris J. 1968. The Logic of Survey Analysis.
New York: Basic Books.Rossi, Peter H., Lipsey, Mark W., and Henry, Gary T. 2019. Evaluation: A Systematic Approach. 8th ed. Newberry Park, CA: Sage Publications.
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