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Any available cookbooks on Bayesian designs?

Robert Bell writes:

I [Bell] just finished “The Emperor of All Maladies” from 2010. One of the sections is captioned with the “In God we trust, all others bring data” quote which is supposedly from Deming. If you haven’t read it, I think you might like it even though the topic is pretty morbid (i.e. cancer).

I was rereading chapter 7 in Bayesian Data Analysis. While the principles there would allow me to “roll my own”, I was wondering whether or not there is now a comprehensive “cookbook” out there that gathers together such analyses for a variety of experimental designs – sort of a Bayesian equivalent to Montgomery’s “Design and Analysis of Experiments”.

My reply:

I don’t know, but now I’m thinking we should put some of this in our forthcoming book, Statistics for Psychology Research. In the meantime, if anyone has any suggestions, feel free to post them in comments.


  1. Umberto says:

    Cool to know that a book on Stats for Psych. research will be available soon. Any date available?

  2. Steve says:

    I’d be really interested to hear more about the new book. What topics will it cover?

  3. It seems to me that one of the ENORMOUS benefits of Bayesian modeling is that it allows you to tailor the model to the available data/experiment and still have a clear theoretically straightforward method for fitting the model (even if the numerical programming can be somewhat daunting at times). So a cookbook of Bayesian modeling would miss the point a little bit. I’m not saying it wouldn’t be useful, but it wouldn’t be as useful as you might think.

  4. Alex says:

    Isn’t the BUGS examples set a bit of a cookbook? It’s not particularly well structured but there are some good recipes in there, which beginners can use to work out how to tailor their own analyses to the data.

  5. Ase Innes-Ker says:

    My old stats teacher has a book on bayesian analysis for psychology: John Kruschke. Not sure how cookbooky it is, but my first glance suggested it holds hands – which is very much John.