Author: Mayo

S. Senn: Personal perils: are numbers needed to treat misleading us as to the scope for personalised medicine? (Guest Post)

Personal perils: are numbers needed to treat misleading us as to the scope for personalised medicine? A common misinterpretation of Numbers Needed to Treat is causing confusion about the scope for personalised medicine. Stephen Senn Consultant Statistician, Edinburgh Introduction Thirty years ago, Laupacis et al1 proposed an intuitively appealing way that physicians could decide how […]

Statistics and the Higgs Discovery: 5-6 yr Memory Lane

I’m reblogging a few of the Higgs posts at the 6th anniversary of the 2012 discovery. (The first was in this post.) The following, was originally “Higgs Analysis and Statistical Flukes: part 2″ (from March, 2013).[1] Some people say to me: “This kind of [severe testing] reasoning is fine for a ‘sexy science’ like high energy physics (HEP)”–as if their statistical inferences […]

Replication Crises and the Statistics Wars: Hidden Controversies

Below are the slides from my June 14 presentation at the X-Phil conference on Reproducibility and Replicability in Psychology and Experimental Philosophy at University College London. What I think must be examined seriously are the “hidden” issues that are going unattended in replication research and related statistics wars. An overview of the “hidden controversies” are on […]

Your data-driven claims must still be probed severely

Below are the slides from my talk today at Columbia University at a session, Philosophy of Science and the New Paradigm of Data-Driven Science, at an American Statistical Association Conference on Statistical Learning and Data Science/Nonparametric Statistics. Todd was brave to sneak in philosophy of science in an otherwise highly mathematical conference. Philosophy of Science and […]

“Intentions (in your head)” is the code word for “error probabilities (of a procedure)”: Allan Birnbaum’s Birthday

Today is Allan Birnbaum’s Birthday. Birnbaum’s (1962) classic “On the Foundations of Statistical Inference,” in Breakthroughs in Statistics (volume I 1993), concerns a principle that remains at the heart of today’s controversies in statistics–even if it isn’t obvious at first: the Likelihood Principle (LP) (also called the strong likelihood Principle SLP, to distinguish it from the […]

Getting Up to Speed on Principles of Statistics

“If a statistical analysis is clearly shown to be effective … it gains nothing from being … principled,” according to Terry Speed in an interesting IMS article (2016) that Harry Crane tweeted about a couple of days ago [i]. Crane objects that you need principles to determine if it is effective, else it “seems that a […]

3 YEARS AGO (May 2015): Monthly Memory Lane

               3 years ago… MONTHLY MEMORY LANE: 3 years ago: May 2015. I mark in red 3-4 posts from each month that seem most apt for general background on key issues in this blog, excluding those reblogged recently[1]. Posts that are part of a “unit” or a group count as one, as in the case of 5/16, 5/19 […]

Neyman vs the ‘Inferential’ Probabilists continued (a)

Today is Jerzy Neyman’s Birthday (April 16, 1894 – August 5, 1981).  I am posting a brief excerpt and a link to a paper of his that I hadn’t posted before: Neyman, J. (1962), ‘Two Breakthroughs in the Theory of Statistical Decision Making‘ [i] It’s chock full of ideas and arguments, but the one that interests […]

3 YEARS AGO (APRIL 2015): MEMORY LANE

MONTHLY MEMORY LANE: 3 years ago: April 2015. I mark in red 3-4 posts from each month that seem most apt for general background on key issues in this blog, excluding those reblogged recently[1], and in green up to 3 others of general relevance to philosophy of statistics (in months where I’ve blogged a lot)[2].  Posts that are part of a “unit” […]