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2024 | OriginalPaper | Chapter

8. Building Multiple Regression Models

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Abstract

Explanatory multiple regression models are used to accomplish two complementary goals: identification of drivers of performance and prediction of performance under alternative scenarios. Multiple regression offers a major advantage over simple regression. Multiple regression accounts for the joint impact of multiple drivers, which provides a truer estimate of the impact of each one individually. Looking at just one driver, as in simple regression, its estimated impact will be much greater than it actually is. A single driver takes the credit for the joint influence of multiple drivers. For this reason, multiple regression provides a clearer picture of influence.

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Appendix
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Metadata
Title
Building Multiple Regression Models
Author
Cynthia Fraser
Copyright Year
2024
DOI
https://doi.org/10.1007/978-3-031-42555-4_8