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The Data-Generating Process and Scientific Inference

In: Advanced Statistics for Health Research

Author

Listed:
  • Richard J. Butler
  • Matthew J. Butler
  • Barbara L. Wilson

Abstract

The Data-Generating Process (DGP) is a description of how an outcome, Y, is determined by independent variables, X, for all the population under consideration. In prior chapters, we saw how sample means, variances, covariances of a subset of those Y s and Xs were merged to generate OLS orthogonal projections (which are the predicted values of Y in the X-plane) to estimate key features of the underlying population DGP. But the population DGP itself is not directly observable. We use sample statistics to make inferences about the population…

Suggested Citation

  • Richard J. Butler & Matthew J. Butler & Barbara L. Wilson, 2023. "The Data-Generating Process and Scientific Inference," World Scientific Book Chapters, in: Advanced Statistics for Health Research, chapter 4, pages 65-82, World Scientific Publishing Co. Pte. Ltd..
    • Handle: RePEc:wsi:wschap:9789811262876_0004
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