Evaluating individual intervention components: making decisions based on the results of a factorial screening experiment
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The multiphase optimization strategy (MOST) is a framework for not only evaluating but also optimizing behavioral interventions. A tool critical for MOST is the screening experiment, which enables efficient gathering of information for deciding which components to include in an optimized intervention. This article outlines a procedure for making decisions based on data from a factorial screening experiment. The decision making procedure is illustrated with artificial data generated to resemble empirical data. The illustration suggests that this approach is useful for selecting intervention components and settings based on the results of a factorial screening experiment. It is important to develop methods for making decisions based on factorial screening experiments. The approach demonstrated here is potentially useful, but has limited generalizability. Future research should develop additional decision making procedures for a variety of situations.
KEYWORDSComparative effectiveness Multiphase optimization strategy Factorial experiments Behavioral interventions
This project was supported by Award Number P50CA143188-3 from the National Cancer Institute and by Award Number P50DA010075-15 from the National Institute on Drug Abuse. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute, the National Institute on Drug Abuse, or the National Institutes of Health. This work has benefitted from discussions with John Dziak and other colleagues at The Methodology Center. The authors thank Amanda Applegate for editorial assistance.
- 9.Wu CFJ, Hamada M. Experiments: Planning, Analysis, and Parameter Design Optimization. New York: Wiley; 2011.Google Scholar
- 11.Kirk RE. Experimental Design: Procedures for the Behavioral Sciences. 4th ed. Los Angeles: Sage; 2013.Google Scholar
- 12.Kugler KC, Trail JB, Dziak JJ, Collins LM. Effect Coding Versus Dummy Coding in Analysis of Data from Factorial Experiments. [Technical Report No. 12–120]. University Park: The Methodology Center, Penn State: The Methodology Center, Penn State; 2012.Google Scholar
- 13.Fisher JO. The Design of Experiments. New York: Hafner; 1971.Google Scholar