Book recommendations for a mid-career/senior biostatistician

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Dear DataMethods community,

I am Ioannis, a medical doctor and resident physician in Dermatology. I have been following this forum regularly and have found the discussions consistently thoughtful, so I thought it was time to participate more actively.

I am looking for advice on choosing a statistics-related book as a gift and would greatly appreciate your suggestions.

The context is the following: the head of the Department of Biostatistics at the University of Heidelberg, Prof. Meinhard Kieser, who has been a central figure in our Master’s program in Biostatistics, will be retiring next year. We will be holding our Master’s graduation ceremony next week, and I would like to give a book both to him and to the current head of the Master’s program as a small, meaningful token of appreciation.

Many books that immediately come to mind (e.g., Statistical Rethinking, From Models to Meaning) are excellent, but they are primarily aimed at students or early-career researchers. Instead, I am hoping to find something that might resonate with a senior, highly experienced biostatistician as well as a mid-career professional (head of the masters program):

For instance something with conceptual depth, something that you found thought provoking or enjoyable, a book that you found meaningful later in your career and maybe you wished you would have read sooner.

Any suggestions would be very welcome. I am particularly interested in books that feel like something one would enjoy owning and revisiting, rather than using as a reference manual.

Many thanks in advance for your thoughts.

Best

Ioannis

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Dear Ioannis!

The following book was indeed thought-provoking for me.

I think it emphasizes the diagnostic point of view from a medical perspective. Before reading it, it wasn’t entirely clear to me what I was actually trying to do with “prediction” models in the context of diagnosis. This book helped me clarify that process, not only in statistical terms but more importantly in historical and epistemological ones.

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Modern Applied Statistics by Venables and Ripley; Elements of Graphing Data by William Cleveland; Kendall & Stuart (a classic in math stat).

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In addition to Franks excellent text Ive enjoyed Gelman’s Regression and Other Stories ROS.pdf

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I second Kendal and Stuart - I don’t think it gets enough attention (especially lately) and I am also a huge fan of Testing Statistical Hypotheses by Lehmann and Romano (Two volume Set) and Statistical Methods in Diagnostic Medicine by Zhou

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Either Radical Uncertainty by John Kay and Mervyn King, or Escape from Model Land by Erica Thompson.

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Thanks for the excellent suggestions so far. What about the Art of Uncertainty from Spiegelhalter? Or Clinical Prediction Models from Steyerberg?

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This one is coming out may be interesting;

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Both are on my desk. I enjoy reading Spiegelhalter (this one and Art of Statistics) - aimed at a general audience, so very different from most of the rest recommended here. My version of the Steyerberg book is 15 years old - I certainly found it useful when I first used it. Is there any updated version?

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2nd edition came out in 2019 - Clinical Prediction Models: A Practical Approach to Development, Validation, and Updating | Springer Nature Link

Edit: I would also add the book on GAMs/mgcv by Wood Generalized Additive Models | An Introduction with R, Second Edition |

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