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A Simulation Framework for the Validation of Research Hypotheses on Net Scoring

In: Targeting Uplift

Author

Listed:
  • René Michel

    (Deutsche Bank AG)

  • Igor Schnakenburg

    (DeTeCon International GmbH)

  • Tobias von Martens

    (Deutsche Bank AG)

Abstract

Since a theoretical examination of scoring approaches may not be sufficient in any case, this chapter focuses on a simulation framework that derives hypothetical data based on real-world data in order to provide suitable data for empirical evaluations of scoring methods and selection approaches. This framework is not necessarily associated with uplift modeling. However, it helps to answer some of the research questions raised in this book, e.g., appropriate (control) group sizes or sampling strategies. The hypothetical data resembles real-world data quite closely but allows for the variation of different parameter values, such as random noise or uplift.

Suggested Citation

  • René Michel & Igor Schnakenburg & Tobias von Martens, 2019. "A Simulation Framework for the Validation of Research Hypotheses on Net Scoring," Springer Books, in: Targeting Uplift, chapter 0, pages 137-146, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-22625-1_6
    DOI: 10.1007/978-3-030-22625-1_6
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