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Statistical Modeling

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Abstract

This chapter starts with a brief essay that reminds us of the nature of statistical modeling and its inherent limitations. Statistical modeling encompasses a wide range of techniques with different levels of complexity. We limit this chapter mostly to an introductory-level treatment of some techniques that have gained prominence in epidemiology. For more in-depth coverage and for other topics we refer to other didactical sources. Every health researcher is likely, at some point in her career, to make use of statistical smoothing techniques, logistic regression, modeling of probability functions, or time-to event analysis. These topics are introduced in this chapter (using Panel 24.1 terminology), and so is the increasingly important topic of cost-­effectiveness analysis.

Keywords

  • Economic Evaluation
  • Probability Function
  • Cost Effectiveness Analysis
  • Multiple Logistic Regression Analysis
  • Incremental Cost Effectiveness Ratio

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

All models are wrong, some models are useful.

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Fig. 24.1
Fig. 24.2
Fig. 24.3
Fig. 24.4
Fig. 24.5
Fig. 24.6
Fig. 24.7

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Correspondence to Jan Van den Broeck M.D., Ph.D. .

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Van den Broeck, J., Fadnes, L.T., Robberstad, B., Thinkhamrop, B. (2013). Statistical Modeling. In: Van den Broeck, J., Brestoff, J. (eds) Epidemiology: Principles and Practical Guidelines. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5989-3_24

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  • DOI: https://doi.org/10.1007/978-94-007-5989-3_24

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