Reviewed by Thoralf Mildenberger (ZHAW)

• Paul. D. Ellis, The Essential Guide to Effect Sizes. Statistical Power, Meta-Analysis and the Interpretation of Research Results. Cambridge University Press, Cambridge 2010. Link to book on publisher’s website.

In the last few years, statistical hypothesis testing – with the p-value still being THE standard for reporting results in many fields of science – has increasingly been criticized. Many researchers have even called for abandoning the “NHST” (Null Hypothesis Significance Testing) approach all together. I think this is going too far as many problems are due to misapplication of the techniques and – perhaps even more importantly – misinterpretation of the results. There is also no consensus on how to replace hypothesis testing with a better methodology – some of the more moderate critics suggest using confidence intervals, but while these are often more informative they are essentially equivalent to hypothesis tests and share some of the problems. This makes it all the more important to highlight difficulties in the correct application and interpretation of statistical methodology. Continue reading