Monthly Archives: August 2021

Should Bayesian Clinical Trialists Wear Error Statistical Hats? (i)


I. A principled disagreement

The other day I was in a practice (zoom) for a panel I’m in on how different approaches and philosophies (Frequentist, Bayesian, machine learning) might explain “why we disagree” when interpreting clinical trial data. The focus is radiation oncology.[1] An important point of disagreement between frequentist (error statisticians) and Bayesians concerns whether and if so, how, to modify inferences in the face of a variety of selection effects, multiple testing, and stopping for interim analysis. Such multiplicities directly alter the capabilities of methods to avoid erroneously interpreting data, so the frequentist error probabilities are altered. By contrast, if an account conditions on the observed data, error probabilities drop out, and we get principles such as the stopping rule principle. My presentation included a quote from Bayarri and J. Berger (2004): Continue reading

Categories: multiple testing, statistical significance tests, strong likelihood principle | 26 Comments

Performance or Probativeness? E.S. Pearson’s Statistical Philosophy: Belated Birthday Wish

E.S. Pearson

This is a belated birthday post for E.S. Pearson (11 August 1895-12 June, 1980). It’s basically a post from 2012 which concerns an issue of interpretation (long-run performance vs probativeness) that’s badly confused these days. Yes, i know I’ve been neglecting this blog as of late, but this topic will appear in a new guise in a post I’m writing now, to appear tomorrow.


Are methods based on error probabilities of use mainly to supply procedures which will not err too frequently in some long run? (performance). Or is it the other way round: that the control of long run error properties are of crucial importance for probing the causes of the data at hand? (probativeness). I say no to the former and yes to the latter. This, I think, was also the view of Egon Sharpe (E.S.) Pearson.  Continue reading

Categories: E.S. Pearson, Error Statistics | 2 Comments

Fair shares: sexual justice in patient recruitment in clinical trials



Stephen Senn
Consultant Statistician
Edinburgh, Scotland

It is hard to argue against the proposition that approaches to clinical research should treat not only men but also women fairly, and of course this applies also to other ways one might subdivide patients. However, agreeing to such a principle is not the same as acting on it and when one comes to consider what in practice one might do, it is far from clear what the principle ought to be. In other words, the more one thinks about implementing such a principle the less obvious it becomes as to what it is.

Three possible rules

Continue reading

Categories: evidence-based policy, PhilPharma, RCTs, S. Senn | 5 Comments

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