Hurricanes have not increased in the North Atlantic

My paper on this subject will finally appear in the Journal of Climate soon. You can see it’s status (temporarily, anyway) at this link.

You can download the paper here.

The gist is that the evidence shows that hurricanes have not increased in either number of intensity in the North Atlantic. I’ve only used data through 2006; which is to say, not this year’s. But if I were to, then, since the number and intensity of storms this past year were nothing special, the evidence would be even more conclusive that not much is going on.

Now, I did find that there were some changes in certain characteristics of North Atlantic storms. There is some evidence that the probability that strong (what are called Category 4 or 5) storms evolving from ordinary hurricanes has increased. But, there has also been an increase in storms not reaching hurricane level. Which is to say, that the only clear signal is that there has been an increase in the variability of intensity of tropical cyclones.

Of course, I do not say why this increase has happened. Well, I suggest why it has: changes in instrumentation quality and frequency since the late 1960s (which is when satellites first went up, allowing us to finally observe better). This is in line with what others, like Chris Landsea at the Hurricane Center, have found.

I also have done the same set of models of global hurricanes. I found the same thing. I’m scheduled to give a talk on this at the American Meteorological Society’s annual meeting in January 2008 in New Orleans. That paper is here.

The Algebra of Probable Inference: Richard T. Cox

This is a lovely, lovely book and I can’t believe it has taken me this long to find and read it (November 2005: I was lead to this book via Jaynes, who was the author that also recommended Stove). Cox, a physicist, builds the foundations of logical probability using Boolean algebra and just two axioms, which are so concise and intuitive that I repeat them here:

1. “The probability of an inference on given evidence determines the probability of its contradictory on the same evidence.”

2. “The probability on given evidence that both of two inferences are true is determined by their separate probabilities, one on the given evidence, the other on this evidence with the additional assumption that the first inference is true.”

Cox then begins to build. He shows that probability can be, should be, and is represented by logic; he shows the type of function probability is, the relation of uncertainty and entropy, and what expectation is. He ends with deriving Lapace’s rule of succession, and argues when this rule is valid and when it is invalid. And he does it all in only 96 pages!. This is one of the rare books that I also recommend you read each footnote. If you have any interest in probability or statistics, you have a moral obligation to read this book.

How to Exaggerate Your Results: Case study #1

In the Tuesday, 6 November 2007 edition of the Wall Street Journal, Pfizer took out a full-page ad encouraging people to “Ask your doctor” about Lipitor, a drug which claims to lower your “risk” of a heart attack (p. A13). In enormous bold print are the words:

Lipitor reduces risk of heart attack by 36%*.

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Following that asterisk on the 36% leads to something interesting:

*That means in a large clinical study, 3% of patients taking a sugar pill or placebo had a heart attack compared to 2% of patients taking Lipitor.

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Congratulations, Pfizer! This ad scores a solid 7 on the Statistical Deception Scale.

First, if you take Lipitor your risk is only lowered by a relative amount, from an already low 2% to a slightly lower 1%. Your real risk is only lowered by 1%. There is a world of difference between that 36% and 1%, and the ad did say, sort of, that the risk was relatively lowered, not lowered absolutely, so it wasn’t terribly deceptive at that point. It’s true, too, that some people might think to themselves, “Ah, any lowering is good, even if it’s only 1%.” More on that sentiment in a moment.

But what most people won’t see, or will ignore, are the smaller words under the bold headline, which say that your risk is lowered “If you have risk factors such as family history, high blood pressure, age, low HDL (‘good’ cholesterol) or smoking.” Aha! This is what ups Pfizer’s ranking on the deception scale.

Thus, in order to get the 1% reduction it turns out that you have to be in a pretty high risk group to begin with; namely, those with “multiple” risk factors. How many risk factors do you have to have before you can hope for the reduction? Two? Three? The ad doesn’t say. Maybe you need all five before you can hope for the reduction. That is the most likely reading of the ad.

What if you don’t have all five? We might guess that your absolute risk reduction is either zero or negligible. We guess this because if people could reduce their risk generally, without belonging to a highly selective group, that Pfizer would have boasted of this. They did not so boast, so etc. etc.

Back to the “any lowering is good” sentiment. On the page opposite the pictures, Pfizer has quite a long list called “POSSIBLE SIDE EFFECTS OF LIPITOR”. Among these new risks are, muscle problems, kidney “problems” or even failure, liver problems, nausea, vomiting, brown colored urine, tiredness, yellowing eyes (!), rash, gas, and others. The key words are these:

Fewer than 3 people out of 100 stopped taking LIPITOR because of side effects.

Well, must I point out that 3 out of 100 is 3%, which is more—67% more!—than the 2% (in the high risk group) who will have a heart attack, and 200% more than the 1% (or so) of the “regular” people who will have a heart attack? I guess I don’t need to. Of course, we can’t figure out, given only the data that Pfizer provides in the ad, what the actual chance is that a regular person will have a heart attack or suffer “side” effects. But there is enough information provided that should severely limit enthusiasm for this drug.

The advertisement also pictures Robert Jarvik, inventor of the “Jarvik artificial heart”, badly in need of a haircut, standing in front of a colorful heart-like object. But he is a celebrity doctor, and isn’t that all you really need to know?