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Selection: Gelman:A [2 articles] 

Publications by author Gelman:A.

Applied regression and multilevel/hierarchical models



Data Analysis Using Regression and Multilevel/Hierarchical Models is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models. The book introduces and demonstrates a wide variety of models, at the same time instructing the reader in how to fit these models using freely available software packages. The book illustrates the concepts by working through scores of real data examples that have arisen in the authors’ own applied research, with programming code provided for each one. Topics ...


The statistical crisis in science

American Scientist, Vol. 102, No. 6. (2014), 460,


Data-dependent analysis—a “garden of forking paths”— explains why many statistically significant comparisons don't hold up. [Excerpt] There is a growing realization that reported “statistically significant” claims in scientific publications are routinely mistaken. Researchers typically express the confidence in their data in terms of p-value: the probability that a perceived result is actually the result of random variation. The value of p (for “probability”) is a way of measuring the extent to which a data set provides evidence against a so-called null hypothesis. ...

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