Bootstrapping Confidence Levels for Hypotheses about Quadratic (U-Shaped) Regression Models

Details Bootstrapping Confidence Levels for Hypotheses about Quadratic (U-Shaped) Regression Models Bootstrapping Confidence Levels for Hypotheses about Quadratic (U-Shaped) Regression Models

2009-12-19

arxiv.org/abs/0912.3880v3

Statistics

Methodology

9 pages, 2 figures

Scientific paper

This paper shows how bootstrapping can be used to derive confidence levels for hypotheses about features of quadratic regression models - such as whether the U-shape is inverted, and the location of optimum values. These confidence levels can be interpreted as probabilities. The bootstrap method is also transparent and flexible - it could easily be applied to a wide variety of different types of models. The transparency can be enhanced by formulating models with directly interpretable coefficients such as the location and value of the optimum. Keywords: Bootstrap resampling; Confidence level; Quadratic model; Regression, U-shape.

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