As I was writing my next column for CHANCE, I decided I will include a methodology box about “using the data twice”. Here is the draft. (The second part is reproduced verbatim from an earlier post on Error and Inference.) Several aspects of the books covered in this CHANCE review [i.e., Bayesian ideas and data analysis, […]

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## on using the data twice…

January 13, 2012## Probability and Bayesian modeling [book review]

March 26, 2020Probability and Bayesian modeling is a textbook by Jim Albert [whose reply is included at the end of this entry] and Jingchen Hu that CRC Press sent me for review in CHANCE. (The book is also freely available in bookdown format.) The level of the textbook is definitely most introductory as it dedicates its first […]

## visual effects

November 2, 2018As advertised and re-discussed by Dan Simpson on the Statistical Modeling, &tc. blog he shares with Andrew and a few others, the paper Visualization in Bayesian workflow he wrote with Jonah Gabry, Aki Vehtari, Michael Betancourt and Andrew Gelman was one of three discussed at the RSS conference in Cardiff, last week month, as a […]

## Measuring statistical evidence using relative belief [book review]

July 22, 2015“It is necessary to be vigilant to ensure that attempts to be mathematically general do not lead us to introduce absurdities into discussions of inference.” (p.8) This new book by Michael Evans (Toronto) summarises his views on statistical evidence (expanded in a large number of papers), which are a quite unique mix of Bayesian principles […]

## full Bayesian significance test

December 18, 2014Among the many comments (thanks!) I received when posting our Testing via mixture estimation paper came the suggestion to relate this approach to the notion of full Bayesian significance test (FBST) developed by (Julio, not Hal) Stern and Pereira, from São Paulo, Brazil. I thus had a look at this alternative and read the Bayesian […]