For those of you who aren't statisticians: D. R. Cox was an absolute legend. Revolutionized the field of survival statistics with his proportional hazards model. Shares 50% of the credit for the Box-Cox test and all the giggles it generates in undergrads. Invented the Cox point process. A zillion other things. His contributions were great and he will be missed.

Edit: I have to edit my comment because calling him an absolute legend doesn't feel like it was doing him justice. I'm not kidding, I don't think I can state how important he was. He's in the top 5 statisticians of all time- everyone's ranking of top 5 varies but Cox is in the top 5 on almost every statistician's list- and will probably still be top 5 until the future is perfectly predictable and there is no need for probability and statistics anymore. There may never be someone that is as productive and with as impactful discoveries. Sure, there will be people that write more papers, but nobody will write as many great papers. Sure, there are other great statisticians that have a few great discoveries named after them, but there are none that have as many great discoveries named after them.

I remember thinking “isn’t it odd that there were several statisticians named Cox with important work?” It didn’t even occur to me that so many fundamentals, over literally decades from the 50s to the 00s, and even popular textbooks like his one on applied statistics, could ALL be from one mind. Amazing.

How can we be sure that people with last name Cox aren't just 200% more likely to provide significant contributions to the field of statistics?

Because David Cox would have written a paper about it if so.

Gertrude Cox is actually also a famous statistician with considerable contributions to the field, so you weren't entirely wrong, but of course David is (was) almost peerless in living memory.

It is kind of crazy how these machine learning people are more famous in the general audience compared to the greats like Cox.

I read his principles of statistics books and I would recommend it to anyone doing data analysis.

Impressive.

The information age has advanced so rapidly, we hardly realize that almost everything that had been invented, was by people just passed or still alive. When I was in college, Claude Shannon still attended information theory seminars. He invented all of digital communications (or nearly so).

I really wish we had a way to keep legends alive longer and help them be happy, healthy, and contribute more to society.

I think it’s kind of beautiful that we all have our limited times to make an impact. We bring our perspectives and use our context to try to move civilization to a more optimal place. Then once we’ve spent all our ideas our perspectives can afford, we give way to the next group of minds. Like an old oak falling under the weight of snow opens room in the canopy for new growth and the decomposing wood provides nutrients for saplings; the absence of old arguments invite new ideas and the theory we leave gives the building blocks.

I don't know if I'd call it beautiful or desirable over a world where we live forever and develop robust mechanisms to ensure our perspectives are forced to change and adapt instead of calcifying and power cannot entrench itself, but I agree that I can appreciate the fact that although people like Dr. Cox and Hans Rosling die, so do tyrants and those irrationally stubborn

This i fear. People who dont like the idea of immortal enforce others to be so. I am not saying the op is of this opinion, its my obsevation.

He lived till 98. At some age cut-off point, shouldn't we be thankful that he lived so long?.

If you consider the first 25 as useless/building stage of life and the next 35 as contributing/productive part. This man lived another 38 years after that (an entire new useful life span for an average human).

> If you consider the first 25 as useless/building stage of life and the next 35 as contributing/productive part.

I never thought I’d read a comment where someone just called their youth worthless. Aside from being reductionist and utterly devoid of empathy, there’s an entire industry built around life extension that disagrees with you.

There are multiple philosophical points.

For someone who lives/interacts with David Cox everyday, the loss is immense.

But OP was referring to 'loss to the society'. When you bring in 'loss to the society', then it is inevitable that you measure their net-positive-contributions-to-society.

Unless you are an outlier (<0.0001%), 25 and below is usually where you are sucking away resources without contributing back (easily measured by net worth or artifacts or offsprings). 25 - 60 is when you are peak contribution (offsprings, net worth, artifacts), after 60 most stop producing (offsprings, artifacts, wealth accumulation). Yes there are outliers to these too.

Now to the controversial. Yes, offspring creation is (the ultimate) productive service to the society. It's the *only* way to keep humanity not going extinct.

Thought experiment: Tomorrow if everyone decides to stop offsprings, humanity is guaranteed to be extinct in 100 years. However, if everyone decides to have a baby or two, humanity will chug along for at least quite a few hundred years (Climate Change is not going to make us extinct)

Not to mention implying that people over 60 aren't contributing or productive.

One might hope that his last act was to calculate the chance of his reaching 99.

Only if we have a way to keep narcissistic terrors from using said method to prolong their awfulness.

Why does one have to be a legend for you to wish that for them?

Because they are useful!

Survival analysis was my first great methodological love. Dr. Cox was an absolute giant in the field.

If you have ever used logistic regression, you can probably credit Cox. He popularized the model during a time when Probit regression was more popular.

For the younger generation, a logistic regression is a neural network without a hidden layer :)

Any specific suggested books by Dr. Cox as someone new but enthusiastic to the field?

Cox had unrivaled breadth across the statistical books that he authored, and I'm far from an expert on his catalog, but I have read three and they are excellent.

- Theory of Design of Experiments is an excellent and non-technical book on experimentation and data collection. Still important in an era of big data!

- Analysis of Survival Data is the book on the Cox model. It is quite technical. I own this book for historical reasons, and I'm glad I read it, but I now recommend Therneau for serious survival statistics.

- Theoretical Statistics w/ Hinkley is still a great mathematical statistics book. Excellent math-stats books are uncommon now, and Cox was a master.

Cox also wrote a few books on stochastic processes that are well regarded, but I'm unfamiliar.

I most recently read Celebrating Statistics: Papers in honour of Sir David Cox on his 80th birthday which is a very thoughtful collection.

Principles of Applied Statistics by D. R. Cox and Christl A. Donnelly

From Cosma Shalizi's review [0]:

> D. R. Cox published his first major book, Planning of Experiments, in 1958; he has been making major contributions to the theory and practice of statistics for as long as most current statisticians have been alive. He is now in a reflective phase of his career, and this book, coauthored with the distinguished biostatistician Christl A. Donnelly, is a valuable distillation of his experience of applied work. It stands as a summary of an entire tradition of using statistics to address scientific problems.

[0] http://bactra.org/reviews/cox-donnelly.html

Sounds incredible. I will surely read this one!

From "A Conversation with George Box" - ------------

The story about that goes back to the time when I was still in England, and David Cox and I were both on the research committee of the Royal Statistical Society. Various people remarked on the fact that Box and Cox were both on the committee and said that we should write a paper together. My recollection is that either David said to me or I said to David, "You know, perhaps we ought to take them up on that." And so, "Yes, OK, let's do that. And what should it be about?" Well, we both knew the story about Box and Cox. This is a story about Box living in a room during the day and Cox living in the same room during the night, and neither of them knew that the landlady was giving the room to two people and getting two rents rather than one. So we said, "Well, obviously the thing to write about is transformations." And that was all we had to begin with. [Laughs] We did something about it. We got as far as the part about the Jacobian, and if you've read that paper ["An analysis of transformations," J. Roy. Statist. Soc. Ser. B 26 (1964) 211-252] you'll know that this part is a little bit tricky, even controversial. We didn't know quite how to deal with that bit, and so it got put to one side. The time passed, years passed; I went to Princeton, and then to Madison. After I had been at Madison a short while, the way I remember it is that David wrote me a letter and said, "Hey, you know that thing we were doing? I think if we went this way, we would be able to do it." And I wrote back and said, "Yeah, I think so," and what about this and what about that, and so on. And so we started working together again on it, and finally we got the paper out.

DeGroot: A classic paper. So it really did start with just the authors' names and built up from there.

Box: Yes. I think we also had sort of a slight conspiracy because I think we both felt it was a bit funny about the Box and Cox notion. David was keener on the likelihood approach and I was keener on the Bayesian approach. So we put both in, and when the discussion came up various people said, "Perhaps the authors would like to say whether they both agree on this" and we were careful not to say. So there was sort of a slight Box-Coxish uncertainty about the whole thing which we thought was amusing. -------

One of the most cited papers in Statistics, the Box-Cox transform (http://www.econ.uiuc.edu/~econ508/Papers/boxcox64.pdf , 18000+ citations) is a power transform just about everybody has employed at one point or another when dealing with non-Gaussian data (builtin function MASS::boxcox in R)

This news truly deserves a HN top black belt. :(

I read Cox and Hinkley's Theoretical Statistics a few months ago and it's such a treat. Might need to buy his Analysis of Binary Data to commemorate.

RIP to a legend. Please respect his memory and resist the urge to regress to Cox jokes.

I fear Scientific American is now preparing an editorial overview of his sins.

This deserves a black banner.