Weekly dose of Judson

NYT's best science writer has a new column up. This time she's looking at the placebo effect.

Are oil companies rational actors?

There are some good pieces out on the economics of oil spills from Jonathan Chait and Ezra Klein, but the best of the bunch is by William Galston:

Second, the oil well now spewing large quantities of crude oil into the Gulf of Mexico lacked a remote-control acoustic shutoff switch used by rigs in Norway and Brazil as the last line of defense against underwater spills. There’s a story behind that. As the Journal reports, after a spill in 2000, the MMS issued a safety notice saying that such a back-up device is “an essential component of a deepwater drilling system.” The industry pushed back in 2001, citing alleged doubts about the capacity of this type of system to provide a reliable emergency backup. By 2003, government regulators decided that the matter needed more study after commissioning a report that offered another, more honest reason: “acoustic systems are not recommended because they tend to be very costly.” I guess that depends on what they’re compared to. The system costs about $500,000 per rig. BP is spending at least $5 million per day battling the spill, the well destroyed by the explosion is valued at $560 million, and estimated damages to fishing, tourism, and the environment already run into the billions.

There’s something else we know, something that suggests an explanation for this sequence of events. After the Bush administration took office, the MMS became a cesspool of corruption and conflicts of interest. In September 2008, Earl Devaney, Interior’s Inspector General, delivered a report to Secretary Dirk Kempthorne that has to be read to be believed. One section, headlined “A Culture of Ethical Failure,” documented the belief among numerous MMS staff that they were “exempt from the rules that govern all other employees of the Federal Government.” They adopted a “private sector approach to essentially everything they did.” This included “opting themselves out of the Ethics in Government Act.” On at least 135 occasions, they accepted gifts and gratuities from oil and gas companies with whom they worked. One of the employees even had a lucrative consulting arrangement with a firm doing business with the government. And in a laconic sentence that speaks volumes, the IG reported: “When confronted by our investigators, none of the employees involved displayed remorse.”

Was leaving out these shut off switches a rational decision? Between direct costs, lawsuits and PR, BP may take a ten figure hit here, but they spent a great deal of money and effort lobbying not to take a measure that, to the casual observer, would seem to have a positive expected value.

Is it possible that, even for huge corporations, the natural distaste for being told what to do is stronger than the desire to maximize utility?

Authorship

I liked today's post by DrugMonkey on authorship. One item that I think is worth considering is that, in complex and multi-author projects, it's actually really hard to allocate credit on a paper by paper basis. That's because credit can't be broken into pieces that precisely fit "First Author", "Senior Author", "Second Author", and "Middle Author".

I have had the good fortune to be involved with some really exceptional co-authors so I can't actually recall a signigicant authorship dispute. But I do think that this highlights the need to rotate people on large projects to do the best to approximate the level of credit that people should get on projects.

But it's not an easy exercise and it gets harder the fewer the number of papers and the more junior the group (as early career researchers are very sensitive to credit allocation when it comes to being evaluated for employment and such things).

"Markets Are Not Magic"

An old post from Mark Thoma that's worth another look.

"Then I came up with a great idea: I could use the fork to spear the food and the spoon to scoop it."

As many others have noted, there is nothing journalists like more than a standard narrative and when reporting on education, there is no narrative more standard than the legend of the good teacher/bad teacher. No matter how complex, every issue can be explained by a disapproving account of an inept instructor or, better yet, a breathless paean to an inspiring educator.

I've mentioned before (here and here), there are some serious issues that need to be addressed (but almost never are) when comparing performance of teachers. Less serious but more annoying is the reporters' wide-eyed amazement at common classroom techniques. Things like putting agendas on the board or calling on students by name without asking for volunteers (see here) or having students keep a journal and relate lessons to their own life (see any article on Erin Gruwell). Things that many or most teachers already do. Things that you're taught in your first education class. Things that have their own damned boxes on the evaluation forms for student teachers.

These techniques are very common and are generally good ideas. They are not, however, great innovations (with a handful of exceptions -- Polya comes to mind) and they will seldom have that big of an impact on a class (again with exceptions like Polya and possibly Saxon). Their absence or presence won't tell you that much and they are certainly nothing new.

"Shape of the earth -- opinions still differ"

I was reminded of Paul Krugman's parody of a New York Times headline when I came to this NYT headline:

"Despite Push, Success at Charter Schools Is Mixed By TRIP GABRIEL"

Followed a few paragraphs later by the money shot:

But for all their support and cultural cachet, the majority of the 5,000 or so charter schools nationwide appear to be no better, and in many cases worse, than local public schools when measured by achievement on standardized tests, according to experts citing years of research. Last year one of the most comprehensive studies, by researchers from Stanford University, found that fewer than one-fifth of charter schools nationally offered a better education than comparable local schools, almost half offered an equivalent education and more than a third, 37 percent, were “significantly worse.”

Although “charter schools have become a rallying cry for education reformers,” the report, by the Center for Research on Education Outcomes, warned, “this study reveals in unmistakable terms that, in the aggregate, charter students are not faring as well” as students in traditional schools.

As I mentioned before, there is reason to believe that this research is biased in favor of charter schools.

If you showed me test results for a new cholesterol-controlling drug in which 20% of the subjects had lower LDL levels than when they started taking the drugs, 51% stayed the same and 37% were "significantly worse," I don't think I would describe the results as 'mixed.'

But, of course, I'm not writing for the New York Times.

Bringing a whole new meaning to the term "Primary Investigator"

From Talking Points Memo:

[Virginia AG] Cuccinelli has launched an investigation into one of the climate scientists who was embarrassed by last year's Climate-Gate controversy -- and in doing so, he may be challenging long-held norms about academic freedom.

Last month, reports The Hook of Charlottesville, the AG requested "a sweeping swath of documents" from the University of Virginia, relating to the climate research work -- funded through state grants -- of Michael Mann.

Mann worked at the university from 1999 to 2005, and now runs Penn State's Earth System Science Center. If he were found to have manipulated data, Cuccinelli could seek to have the research money -- plus damages -- returned to the state.

It's not clear that there's much evidence of that, however. The climate-gate emails showed some scientists discussing ways to keep views skeptical of global warming out of peer-reviewed journals, among other things -- but they did not show outright fraud. Nor did they undermine the broad expert consensus that man-made warming is occurring and must be addressed.

Mann's work is currently being investigated by Penn State. In a recent USA Today story, he defended it, saying that though errors might exist, they were not fraudulent.

Undiagnosed diseases

One thought that I have often had about prescription claims databases is that we often can't do anything with missing data. If a patient in such a database has undiagnosed hypertension, for example, it's unclear how to handle it. This is in stark contrast to cohort studies where a missing blood pressure reading is a clear case of missing data and straightforward multiple imputation may do wonders.

So I wonder if Andrew Gelman's idea for count data could be adapted for this purpose?

Or would we be buried by an excessive number of assumptions that might be required to make it work in these settings?

Prelinking Nick Krafft

When I get my thoughts on the subject sorted out I plan to write some posts on maximum utility and fitness landscapes. When I do, I'll certainly want to link to this post I saw on Economist's View:

In which I “attack old-fashioned economics,” i.e. utility maximization, by Nick Krafft: At an off-campus discussion toward the end of my senior year of college, the topic of behavioral economics came up. Leading the discussion was a professor of mine, David Ruccio- whose blog I link to regularly- who argued that to really move forward with these iconoclast ideas, we still have to get rid of the max u thing- it’s holding everything back. I didn’t really agree with him at the time, or I just didn’t know, but a recent panel I attended helped clarify why Ruccio, and other heterodox economists before him, are right, even if the panelists themselves don’t want to see it it or admit.

Hypertension or Blood Pressure?

So which one do you use in your statistical models? Sometimes, in diagnosis based data sets, you don't have a choice (Hypertension is a diagnosis but blood pressure may not be captured).

It seems like a simple question but it includes a lot of complexity. The binary variable is well understood, known to be a relevant change in patient characteristics and can account for things like medication treatment. The continuous variable, whule it has a lot more information, needs some assumptions on spacification. For example, can we really assume linearity of an association between blood pressure and a clinical outcome? If we only have treated blood pressure is that the parameter of interest or is it the "underlying level of blood pressure"? If the later, we have a messy missing data problem.

I admit, as a statistics guy, I strongly incline towards the continuous version of the variable. But it is not at all clear to me that it is always the dominant choice for dealing with these types of varibles.

Landscapes and Lab Rats

In this post I discussed gradient searches and the two great curses of the gradient searcher, small local optima and long, circuitous paths. I also mentioned that by making small changes to the landscape being searched (in other words, perturbing it) we could sometimes (with luck) improve our search metrics without significantly changing the size and location of our optima.

The idea that you can use a search on one landscape to find the optima of a similar landscape is the assumption behind more than just perturbing. It is also the basis of all animal testing of treatments for humans. This brings genotype into the landscape discussion, but not in the way it's normally used.

In evolutionary terms, we look at an animal's genotype as a set of coordinates for a vast genetic landscape where 'height' (the fitness function) represents that animal's fitness. Every species is found on that landscape, each clustering around its own local maximum.

Genotype figures in our research landscape, but instead of being the landscape itself, it becomes part of the fitness function. Here's an overly simplified example that might clear things up:

Consider a combination of two drugs. If we use the dosage of each drug as an axis, this gives us something that looks a lot like our first example with drug A being north/south, drug B being east/west and the effect we're measuring being height. In other words, our fitness function has a domain of all points on our AB plane and a range corresponding to the effectiveness of that dosage. Since we expect genetics to affect the subjects react to the drugs, genotype has to be part of that fitness function. If we ran the test on lab rats we would expect a different result than if we tested it on humans but we would hope that the landscapes would be similar (or else there would be no point in using lab rats).

Scientists who use animal testing are acutely aware of the problems of going from one landscape to another. For each system studied, they have spent a great deal of time and effort looking for the test species that functions most like humans. The idea is that if you could find an animal with, say, a liver that functions almost exactly like a human liver, you could do most of your controlled studies of liver disease on that animal and only use humans for the final stages.

As sound and appealing as that idea is, there is another way of looking at this.

On a sufficiently high level with some important caveats, all research can be looked at as a set of gradient searches over a vast multidimensional landscape. With each study, researchers pick a point on the landscape, gather data in the region then use their findings to pick their findings and those of other researchers to pick their next point.

In this context, important similarities between landscapes fall into two distinct categories: those involving the positions and magnitudes of the optima; and those involving the search properties of the landscape. Every point on the landscape corresponds to four search values: a max; the number of steps it will take to reach that max; a min; and the number of steps it will take to reach that min. Since we usually want to go in one direction (let's say maximizing), we can generally reduce that to two values for each point, optima of interest and time to converge.

All of this leads us to an interesting and somewhat counterintuitive conclusion. When searching on one landscape to find the corresponding optimum of another, we are vitally interested in seeing a high degree of correlation between the size and location of the optima but given that similarity between optima, similarity in search statistics is at best unimportant and at worst a serious problem.

The whole point of repeated perturbing then searching of a landscape is to produce a wide range of search statistics. Since we're only keeping the best one, the more variability the better. (Best here would generally be the one where the global optimum is associated with the largest region though time to converge can also be important.)

In animal testing, changing your population of test subjects perturbs the research landscape. So what? How does thinking of research using different test animals change the way that we might approach research? I'll suggest a few possibilities in my next post on the subject.

A good Bayesian Textbook?

Say that one wanted to teach Pharmacoepidemiology students about Bayesian statistics. Say further that it was important that the book be clear and easy to follow. Are there any alternatives to Gelman and Hill (which is clear but remarkably free of drug related examples)?

Just wondering . . .

Carbon Sequestration, Lap Band Surgery and the Seductive Allure of the Grand, Deferred Solution

There's a paper out (discussed here) which claims that (according to the Guardian):

[G]overnments wanting to use CCS have overestimated its value and says it would take a reservoir the size of a small US state to hold the CO2 produced by one power station.

Previous modelling has hugely underestimated the space needed to store CO2 because it was based on the "totally erroneous" premise that the pressure feeding the carbon into the rock structures would be constant, argues Michael Economides, professor of chemical engineering at Houston, and his co-author Christene Ehlig-Economides, professor of energy engineering at Texas A&M University

We'll see if this actually kills support for CCS, but even before the paper came out, the popularity of the idea was a clear example of Grand Deferred Solution Syndrome (GDSS).

GDSS actually requires at least two solutions. The non-GDSs need to be simple, practical, available for immediate implementation, with high likelihoods of success. The GDS (usually produced by a marketing department or think tank, though spontaneous GDS formation has been observed) does not need to be simple or practical. Its implementation date should be distant and open-ended and its likelihood of success can be anywhere from small to negligible. Sufferers of GDSS will opt for for the GDS even when its chances are one or more orders of magnitude lower than any of the non-GDSs.

Notable examples of non-GDSs include carbon taxes, plug-in hybrids and diet & exercise.* Notable examples of GDSs include fuel cell cars, liposuction and about twenty percent of solutions using the phrase "market forces."

Almost everyone has suffered a few bouts of GDSS, but cases involving climate change may be reaching pandemic proportions.


* This does not apply to those suffering from certain diagnosed medical conditions and eating disorders. For those people, extreme measures may be the only reasonable option.

Predicting the spread

Have you ever been working on a problem and had that nagging feeling that you're missing an obvious solution? Well, I'm having one of those moments now. I'm working on a project that, though it has nothing to do with sports or betting, is analogous to the following:

You want to build a model predicting the spread for games in a new football league. Because the line-up of teams is still in flux, you decide to use only stats from individual teams as inputs (for example, an indicator variable for when the Ambushers play the Ravagers would not be allowed). In other words, you're using data from individuals to predict a metric that is only defined for pairs.

Assume there are around fifty teams and each team has played all of the others exactly one time.

This feels like stat 101 but I can't recall seeing another problem like it. Anyone out there have any suggestions?

A serious discussion of the role of barter in health care

Last week I suggested that someone should dig into candidate Lowden's suggestion more deeply. I'm glad to say someone has.

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I'm amazed that no one in the audience seemed to know what a chicken ranch was.

David Brooks' 100K statistic explained

If you follow this sort of thing, you may recall that a few weeks ago, David Brooks claimed that "Over the last 10 years, 60 percent of Americans made more than $100,000 in at least one of those years, and 40 percent had incomes that high for at least three." based on research by Stephen J. Rose. It was one of those statistics that just looks wrong and it turns it was, though the fault seems to lie mainly with Rose's less-than-clear prose and his algorithm for calculating adjusted household income for individuals (an individual living alone could make considerably less than six figures and still have an adjusted household income of 100K).

Andrew Sprung (who was on this from the beginning) has the details:

I should not have cast my inference that Brooks was misquoting Rose as a near-certainty without being able to verify it. Literally, there was no misquote -- or rather a minor one, converting Rose's "fully 60 percent of adults had at least one year in which their incomes were at least $100,000" to a more active verb formulation: "Over the last 10 years, 60 percent of Americans made more than $100,000." Brooks' re-cast also edits out a ghost of pronoun slippage in Rose's studiedly vague formulation: "adults" had years in which "their" incomes were over $100k. While "their" grammatically agrees with "adults," keeping both in the plural somehow highlights the elision by which household income (the term Rose uses in earlier writings citing similar statistics) becomes the income enjoyed by the individuals in the household.

(h/t to Brad DeLong)

Fitness Landscapes, Ozark Style

[Update: part two is now up.]

I grew up with a mountain in my backyard... literally. It wasn't that big (here in California we'd call it a hill) but back in the Ozarks it was a legitimate mountain and we owned about ten acres of it. Not the most usable of land but a lovely sight.

That Ozark terrain is also a great example of a fitness landscape because, depending on which side you look at, it illustrates the two serious challenges for optimization algorithms. Think about a mountainous area at least partially carved out by streams and rivers. Now remove all of the rocks, water and vegetation drop a blindfolded man somewhere in the middle, lost but equipped with a walking stick and a cell phone that can get a signal if he can get to a point with a clear line of sight to a cell tower.

With the use of his walking stick, the man has a reach of about six feet so he feels around in a circle, finds the highest point, takes two paces that direction then repeats the process (in other words, performs a gradient search). He quickly reaches a high point. That's the good news; the bad news is that he hasn't reached one of the five or six peaks that rise above the terrain. Instead, he has found the top of one of the countless hills and small mountains in the area.

Realizing the futility of repeating this process, the man remembers that an engineer friend (who was more accustomed to thinking in terms of landscape minima) suggested that if they became separated he should go to the lowest point in the area so the friend would know where to look for him. The man follows his friend's advice only to run into the opposite problem. This time his process is likely to lead to his desired destination (if he crosses the bed of a stream or a creek he's pretty much set) but it's going to be a long trip (waterways have a tendency to meander).

And there you have the two great curses of the gradient searcher, numerous small local optima and long, circuitous paths. This particular combination -- multiple maxima and a single minimum associated with indirect search paths -- is typical of fluvial geomorphology and isn't something you'd generally expect to see in other areas, but the general problems of local optima and slow convergence show up all the time.

There are, fortunately, a few things we can do that might make the situation better (not what you'd call realistic things but we aren't exactly going for verisimilitude here). We could tilt the landscape a little or slightly bend or stretch or twist it, maybe add some ridges to some patches to give it that stylish corduroy look. (in other words, we could perturb the landscape.)

Hopefully, these changes shouldn't have much effect on the size and position of the of the major optima,* but they could have a big effect on the search behavior, changing the likelihood of ending up on a particular optima and the average time to optimize. That's the reason we perturb landscapes; we're hoping for something that will give us a better optima in a reasonable time. Of course, we have no way of knowing if our bending and twisting will make things better (it could just as easily make them worse), but if we do get good results from our search of the new landscape, we should get similar results from the corresponding point on the old landscape.

In the next post in the series, I'll try to make the jump from mountain climbing to planning randomized trials.

* I showed this post to an engineer who strongly suggested I add two caveats here. First, we are working under the assumption that the major optima are large relative to the changes produced by the perturbation. Second our interest in each optima is based on its size, not whether it is global. Going back to our original example, let's say that the largest peak on our original landscape was 1,005 feet tall and the second largest was 1,000 feet even but after perturbation their heights were reversed. If we were interested in finding the global max, this would be be a big deal, but to us the difference between the two landscapes is trivial.

These assumptions will be easier to justify when start applying these concepts in the next post in the series. For now, though, just be warned that these are big assumptions that can't be made that often.

And my second favorite quote on lying

Comes from Dashiell Hammett (who, of course, had his own Hellman connection). You'll find it in the Continental Op story, "Golden Horseshoe."

"I was reading a sign high on the wall behind the bar:

ONLY GENUINE PRE-WAR AMERICAN AND BRITISH WHISKEYS SERVED HERE

I was trying to count how many lies could be found in those nine words, and had reached four, with promise of more."

Distributions and outliers

John Cook has an old but good post on the issues that even well behaved normal distributiosn can have have in the extremes. I would tend to argue that these extreme outliers (women over 6' 8", for example) probably are due to some process that is rare (i.e. a genetic mutation, an extreme environmental exposure) and so the real height distribution is a mixture of several underlying distributions with latent (or unobserved variables).

But this line of thinking is actually dangerous. After all, with enough latent variables I can model almost any distribution as a sum of normal distributions. And, if I can't observe these variables, how do I know that they exist?

So I guess this is one place where my intuitions are precisely wrong for handling the problem.

Best quote ever on lying

Matt Springer's review got me to thinking about Mary McCarthy's take on Lillian Hellman

"Every word she writes is a lie, including and and the."

(with thanks to the good people at wikiquotes)

Fox News covers quantum physics. What could possibly go wrong?

Via Felix Salmon, Matt Springer thinks he has a winner:

The Worst Physics Article Ever

Ladies and gentlemen, I give you the worst physics news article I have ever seen:

Freaky Physics Proves Parallel Universes Exist

Every word in the title is wrong but "physics". It's not freaky, doesn't prove anything we didn't already know, and has nothing to do with parallel universes nor does it shed any light the question of their possible existence.

Look past the details of a wonky discovery by a group of California scientists -- that a quantum state is now observable with the human eye -- and consider its implications: Time travel may be feasible. Doc Brown would be proud.

Quantum states are visible to the naked eye all the time. Neon signs, laser pointers, and all kinds of other devices show quantum behavior at the macroscopic level. What this UC Santa Barbara group has done is impressive and important - they've put a tiny but macroscopic object into a superposition of macroscopic quantum states. This is a big deal, but the difference between this and everyday single-atom quantum
mechanics is just one of scale. It's not new physics. And time travel? It's a category error on the scale of a reporter watching the Ottawa Senators play hockey and writing an article claiming they were the new lawmaking body of Canada.

Read more here.

In games of perfect information, bluffing is a really bad idea

But that seems to be the Republican strategy on financial reform. Jonathan Chait has the details:

So wait. Republicans think they can limit the political damage of a filibuster if they reach a bipartisan deal. But what incentive do the democrats have to reach a deal? If they can force the Republicans to maintain a filibuster, why not keep the issue going until November? The strategy here seems to be, take a political hit by opposing popular legislation, and then hope that somehow this will strengthen the party's hand in the negotiations to follow. How will this work? It's like trying to bluff your opponent in poker when both you and he know he has the stronger hand.

What's more, Republicans are no longer even pretending to be able to hold the line after today's vote. This is amazing:

McConnell secured a commitment from his conference to hold together in opposition on the first vote, but all bets are off after that, aides acknowledge. McConnell’s challenge after Monday is preventing moderates such as Snowe and Sen. Susan Collins (R-Maine) from breaking away and weakening Republican leverage.

Now that the Democrats know the Republicans are planning to defect after the first vote, why on Earth would they compromise? Moreover, what is the point of taking the hit by filibustering reform in the first place? It could work, in theory, if you could bluff the Democrats into thinking the GOP might hold the line indefinitely. But I'm pretty sure the Democratic party has access to articles published in Politico, which means the jig is up. So now the Republicans are trying to bluff in poker when they and their opponent know they have the weaker hand, and their opponent has heard them admit that their strategy is to bet for a couple rounds and fold before the end. Why not just cut their losses now? This makes zero sense.

The roots of Apple's business model

Click for the punchline.

"Any color you want as long as it's black"

Following up on Joseph's post, I have two points about SAS's graphics:

First, as bad as they are now, you should have seen them in the early Nineties;

Second, I think the graphics are a pretty good indication of the culture of SAS, a large, privately-held company with an effective monopoly over much of its market. SAS does good work and has an incredible record of innovation but is (in the words of some of its employees) a benevolent dictatorship. The company's attitude has always been we will decide what you need and what's a fair price for it.

I don't mean this as a slam against SAS. After almost twenty years you can put me down as a satisfied customer. It's a good company to work with and, by all accounts, a great company to work for. I don't think going public would make SAS a better company, but I do think it would make it do some things better.

SAS graphics

Okay, it is barely possible to make a decent looking SAS graphic with a half page of code, painfully specified to remove the abjectly painful default look. So imagine my susrpise when R and STATA do good looking graphics with a one line command. Sure, it might occasionally be a long line but still . . . Even EXCEL does this a lot better.

Why is SAS different?

It might seem like a minor point but there is a fair bit of truth to the idea that (easy to use) graphical represenations of data are extremely helpful.

The longer I work with SAS (since 1997) the more I wonder about this . . .

Weight of evidence

One of the annoying things in bio-medicine is that we often cannot replicate findings in a quick or efficient way. Unlike, for example, many areas of physics, an unusual finding can't be looked at quickly. So what do you do with a marginal finding?

Say for example, p=0.045 and conservative analytic approaches (such as BMA or LASSO regression) exclude this parameter?

If you publish it then you risk it being oversold and creating confusion.

If you don't publish it then you might join a long list of other people who ignore an important association.

Both alternatives seem unsatisfactory in the absence of a "hypothesis generation" tag for papers. I like the clinical pharmacology literature for these papers as the best of the alternatives but wish that it'd be cleaner.

A chicken in every pot, a couple more for your HMO

Sue Lowden, the candidate who is currently on track to become the next senator from Nevada recently said about health care:

"And I would have suggested, and I think that bartering is really good. Those doctors who you pay cash, you can barter, and that would get prices down in a hurry. And I would say go out, go ahead out and pay cash for whatever your medical needs are, and go ahead and barter with your doctor."

My first thought was that she meant 'barter' in the figurative sense, that patients should try to cut a deal with their doctors, not that patients should literally give doctors goods and services in lieu of cash.

I was mistaken:

The campaign of Senate candidate Sue Lowden (R-NV) is continuing to stand by Lowden's call for the use of the barter system as a means to bring down health care costs.

On Monday, Lowden doubled down on the barter idea: "You know, before we all started having health care, in the olden days, our grandparents, they would bring a chicken to the doctor. They would say I'll paint your house."

[TPM] asked Lowden spokesperson Crystal Feldman how this could ever be a workable policy, in an era of costly procedures, tests, pharmaceuticals and provider networks? "Americans are struggling to pay for their health care, and in order to afford coverage we must explore all options available to drive costs down," Feldman told TPMDC in an e-mail.

Feldman continued: "Bartering with your doctor is not a new concept. There have been numerous reports as to how negotiating with your doctor is an option and doctors have gone on the record verifying this. Unfortunately, Harry Reid's failed leadership forces us to take drastic measures. The fact remains that instead of producing a health care solution Americans support, Harry Reid spends his time focusing on attacking his biggest threat to another six years in Washington, Sue Lowden."

Aside from comic potential here (there are a lot of services you can barter for in Nevada), this suggests an interesting thought experiment:

Assuming that medical costs were driven by individual doctors and not by hospitals and drug companies (which really can't be bartered with), what would the introduction of barter do to the economics of health care? I would think that the introduction of wide-scale bartering would make the market less efficient and would produce more maldistribution of resources. Is this always true or is this another case where the strange economics of health care produce counter-intuitive results? And what would the other consequences be?

Given that there are approximately eight gazillion economics blogs out there, is there any chance that someone who knows what he or she is talking about could answer this one for us?

Financial reporting done right

With relevant facts, important context, smart commentary and lots of obscenity (some of which is not that effectively bleeped out so you might want to wait until you get home to watch this).

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Journal Impact Factors

Candid Engineer has a post on impact factors. I find the variability of impact factors by field quite frustrating as it often neglects the field specific differences in publication style. Take, for example, the field of statistics. I have yet to find a statistician who would not be proud of an article in the Journal of the American Statistical Society (JASA). It has an impact factor of 2.3; this does not compare favorably with (for example) Epidemiology (IF=5.4) which also publishes methodological papers. But the impact factor approach understates the effort required to beuild on or develop methods -- more sophisiticated methods take a lot longer to work their way into the literature.

In any case, comparing JASA to the New England Journal of Medicine (IF=50!!) makes it clear that the field has a lot to do with the impact of a journal.

So what do you do when you are on the borders of a field?

It's a tricky problem . . .

Tragedy of the grading commons

Unless things have changed radically over the past few years, there's a simple way of determining which teachers are grading the hardest and/or assigning the most homework: just go to parent/teacher night and look for the longest line of concerned or angry parents.

This is not to say that there is no positive feedback; you will have parents who will thank you for keeping standards high and will offer their sincere support, but they will be the minority and more importantly, their per capita impact is less because of the nature of administrators.

As I mentioned in an earlier post, there are very few promotions available to teachers. Administrator is one of the few exceptions, but once you've made the jump into administration the situation changes radically.

Here is some context from the Bureau of Labor Statistics:

Education administrators advance through promotion to higher level administrative positions or by transferring to comparable positions at larger schools or systems. They also may become superintendents of school systems or presidents of educational institutions.
...

In May 2008, elementary and secondary school administrators had median annual wages of $83,880. The middle 50 percent earned between $68,360 and $102,830. The lowest 10 percent earned less than $55,580 and the highest 10 percent earned more than $124,250.

In May 2008, postsecondary school administrators had median annual wages of $80,670. The middle 50 percent earned between $58,940 and $113,860. The lowest 10 percent earned less than $45,050 and the highest 10 percent earned more than $160,500.

When I first decided to go into teaching I asked a retired superintendent I knew for advice. The first thing he told me was, "Never trust a superintendent; they'll lie to your face." I think he was being just a bit harsh but I understand his position. Administrators live in an intensely political world where the right move can double their incomes and the wrong one can get them demoted or fired. It tends to test character.

Under these circumstances, you can understand how frightening an angry parent can be. When a mother and father storm in and demand to talk to the principal, they bring considerable pressure to bear. Enough pressure that even a dedicated educator (and most administrators fall into that category) has to be tempted to cave.

These tense conferences are often the result of an A student receiving a B, and they, in turn, often result in an equally tense principal-teacher conference.

I have never heard of an angry conference caused by an A.

Like a well-maintained commons, high educational standard are in everyone's best interests. Unfortunately, just as it is in the best interest of the individual farmer to overuse common land, so it is in the best interest of individual parents to see their children's grades inflated.

I haven't seen any recent reform proposals that will address that problem; I have seen quite a few that will make it worse.

Who could have seen this one coming?

Apparently the competition for students willing to pay huge tuitions might occasionally lead to a drop in academic standards.

From the New York Times:

Over the last 50 years, college grade-point averages have risen about 0.1 points per decade, with private schools fueling the most grade inflation, a recent study finds.

The study, by Stuart Rojstaczer and Christopher Healy, uses historical data from 80 four-year colleges and universities. It finds that G.P.A.’s have risen from a national average of 2.52 in the 1950s to about 3.11 by the middle of the last decade.

For the first half of the 20th century, grading at private schools and public schools rose more or less in tandem. But starting in the 1950s, grading at public and private schools began to diverge. Students at private schools started receiving significantly higher grades than those received by their equally-qualified peers — based on SAT scores and other measures — at public schools.

Career paths, educational reform and unintended consequences

This post by Joseph about career paths for researchers reminded me of some disturbing trends in career paths on the other side of academia, teaching.

In primary and secondary education, you can have a completely successful career by any conceivable standard and never get a single promotion. You can easily spend your entire professional life doing the same job with the same title. That might even be the ideal.

For a field requiring a degree, additional coursework and certification, this is an extraordinarily limited career path. To make up for that we have traditionally offered the following:

1. Reliable income that increases at an agreed-upon rate annually.

2. A high level of job security after a certain number of years (though this is somewhat offset by low job security before reaching tenure).

As well as creating a career path that didn't depend on promotion (and therefore largely avoided the Peter Principle), this emphasis on deferred, but steady compensation meant schools could minimize their investment in new, untested personnel (most really disastrous teachers do not make it to the tenure mark).

Two of the central tenets of the current move for education reform are elimination of tenure and replacing raises based on experience and education with merit pay. This leaves us with a career path that offers no real chance of promotion, no job security and wildly variable pay based on metrics that are largely out of the teacher's control and can easily be gamed by a biased administrator (see here).

Research Scientists

In the comments on a post on the unintended consequences of increasing post-doctoral salaries, Drug Monkey comments:

I also want to reiterate that at least 70% of the arguments going on here are complaining about the postdoc as a short training stint morphing into a substantial part of, if not the very pinnacle of, a science *career*. If this is the root of your problem, whinging for small raises ain't solving the issue. I've made myself quite clear that I think the lack of a career scientist job track is a horrible situation that bears fixing..and would save the NIH money to boot.

I think that this is really insightful. If we want to have a strong body of directed semi-independent researchers (currently the ground held by post-docs) then it might make sense to formalize the career path. My only thought is whether the new "research scientist" would end up looking a lot like a traditional professor?

On the other hand, so long as the grant system is in the present form, it's rather hard to argue for reform as the financial incentives are pretty well aligned towards making researchers who repeatedly win grants very valuable to their institutions.

And you thought you didn't want to know how they made sausage...

The New York Times has an interesting article on the world's most expensive coffee.

A discussion you ought to be following

Bruce Bartlett and Mark Thoma continue their analyses of the relationship between think tanks, the media and economics.

Here's Bartlett:

Conservatives also realized that putting out a study saying the exact opposite of a liberal study was sufficient to muddy the water and prevent a reporter from drawing a clear conclusion from the liberal study. It didn't matter that the liberal study was done by a preeminent scholar in the field and the conservative study was done by a glorified intern. All that mattered is that they came to opposite conclusions, thus leading to on-the-one-hand/on-the-other-hand stories that everyone hates but the media won't stop writing.

Conservatives understand--better than liberals, I think--that most stories are lucky to last one news cycle. If the reporter later decides that the liberal study was really worthwhile and the conservative one was worthless, he isn't going to go back and do another article on the subject. It's water over the dam.

Parenthetically, I would add that the talking head approach to policy debate on the cable news channels reinforces all the negative aspects of this development. Once upon a time, I used to do a lot of cable interviews. At first, I was often paired with people I knew at other think tanks who were slightly more liberal than I am. But because we both shared common facts and knew the limits of what could be demonstrated through serious academic research, we naturally tended to agree with each quite a bit.

Having two guests who agree with each other is the last thing cable channels want; they want their guests to be 180 degree polar opposites. So gradually I noticed that I was no longer being paired with peers from liberal think tanks, but people I had never heard of who were identified as "Democratic consultant" or something like that. Such people clearly knew virtually nothing about the subject we were discussing and were just there to endlessly repeat talking points that someone gave them.

And here's Thoma's reply:

Some of the people on these shows aren't qualified to speak as economists, but they get called again and again because they can spout talking points in an entertaining fashion. Paul Krugman paired against journalist Robert Samuelson* in a CNN debate on the deficit a week or so ago is an example of this (though from what I saw it's not clear that Samuelson satisfies the "in an entertaining fashion" constraint). Menzie Chinn was certainly frustrated by the pairing:

Nonetheless, overarching all this is a simple question. Why do we ascribe any credibility to a person with an undergraduate degree in political science (what is called Government at Harvard) in the area of economics (let alone accounting)? (The question is inspired by watching the debate between Professor Krugman and Mr. Samuelson on Fareed Zakaria GPS yesterday...)

I'm not sure what the answer is. The elevation of entertainment over facts isn't going to change as that is the most profitable strategy for the networks, and economists are unlikely to become more entertaining.

Though it won't solve the problem, one force helping to counteract the elevation of entertainment over facts is a pair of the most entertaining shows on television, the Daily Show and the Colbert Report. Not only do these shows routinely savage cable news channels for sensationalism and lack of content, they often provide more factual context in their satirical coverage than you'll see on CNN et al.

* I wonder if anyone at CNN has confused Robert Samuelson with Paul Samuelson?

Another reason to abolish tenure

You may have seen this story from Inside Higher Ed (via Andrew):

The biology professor at Louisiana State University at Baton Rouge gives brief quizzes at the beginning of every class, to assure attendance and to make sure students are doing the reading. On her tests, she doesn't use a curve, as she believes that students must achieve mastery of the subject matter, not just achieve more mastery than the worst students in the course. For multiple choice questions, she gives 10 possible answers, not the expected 4, as she doesn't want students to get very far with guessing.

Students in introductory biology don't need to worry about meeting her standards anymore. LSU removed her from teaching, mid-semester, and raised the grades of students in the class. In so doing, the university's administration has set off a debate about grade inflation, due process and a professor's right to set standards in her own course.

Anyone who has spent time behind a podium can give you examples of parents and administrators pressuring teachers to raise a students' grades. The most egregious case I know of took place at a highly prestigious and very pricey prep school, but even in public schools in the days before school choice, a call from a parent to a principal about a grade would often result in an unpleasant employer-employee chat and the loss of a badly needed hour of grading and lesson planning.

I remember those meetings, and I remember thinking how much easier it would have been to stand up to that pressure if only the administrator had had more authority to fire teachers. Thank God for education reform.

Bartlett on the intellectual decline and political rise of think tanks

Over at Forbes, Bruce Bartlett provides an insightful insider's view of the development of the modern think tank. Mark Thoma adds his comments here.

Quote of the day on financial innovation

Felix Salmon is blunt:

In the world of credit, innovation generally consists of taking risky stuff, waving some kind of diversification and/or overcollateralization magic wand, and ending up with something which is (a) meant to be safer, and (b) much more difficult to analyze on a fundamental basis: you end up having to use models instead. And models have a tendency to break.

While on the subject of evolution...

I can't miss a chance to recommend Ian Stewart's "Through the Evolvoscope," a clever and elegant discussion of fitness landscapes. I believe this originally appeared in Stewart's Scientific American column, but you can find it in Another Fine Math You've Gotten Me Into.

Way cool.

Is Tea Party extremism simply aspect dominance?

It has been widely suggested that the coverage of the Tea Party has been focused on a few offensive and unrepresentative cases. Many of the arguments have gone something like this (from the LA Times:

A new Gallup Poll out this morning of 1,033 finds nothing fringe about self-proclaimed Tea Party adherents; they are slightly more likely to be employed, male and definitely more conservative. But otherwise Gallup's Lydia Saad writes, "their age, educational background, employment status,and race -- Tea Partiers are quite representative of the public at large."

But in an excellent post, Tom Schaller at FiveThirtyEight has a different take:

But the Gallup results only confirm that tea partiers are "mainstream" in their demographics, when what really matters are their attitudes. Results released Friday of a new multi-state poll of white voters conducted by the University of Washington's Christopher Parker paint a more complicated picture. The survey asked white respondents about their attitudes toward the tea party movement--and their attitudes toward non-whites, immigrants and homosexuals.

Evolution in the Lab

I try to link to pretty much everything that appears in Olivia Judson's Wild Side, but this piece on the implications of the continued evolution of lab animals should be particularly interesting to readers of this site.

A second area where laboratory evolution can be a serious problem is in the study of subjects like the evolution of aging, and the diseases associated with it. For example, the study of laboratory populations may give a misleading impression of how easy it is to extend lifespans: since laboratory organisms tend to have unnaturally short lifespans, discovering ways to make them live longer may not be especially informative. We may simply be reversing the unnatural shortening that we created in the first place, a view supported by the fact that selection to increase lifespan in laboratory populations often simply restores it to levels seen in the wild.

Definitely worth a look.

You can always get the answer you want if you ask the right question

In today's Wall Street Journal op-ed page, Arthur C. Brooks claims that most Americans oppose progressive taxation. This would seem to contradict most recent polling on the subject but Brooks has his own data:

A 2009 survey conducted by the polling firm Ayers-McHenry asked respondents to choose which of the following statements came closer to their views: "Government policies should promote fairness by narrowing the gap between rich and poor, spreading the wealth, and making sure that economic outcomes are more equal"; or "Government policies should promote opportunity by fostering job growth, encouraging entrepreneurs, and allowing people to keep more of what they earn." Respondents chose the second option over the first, 63% to 31%.

Jonathan Chait responds:

Ayers-McHenry is a Republican polling firm, and the question Brooks cites is an advocacy poll, not a legitimate survey of public opinion. Public opinion experts understand that loading the terms of a question can produce almost any result. The question cited in this poll is filled with loaded language to an almost comical degree.

Straightforward measure of public opinion show strong public support for a progressive tax system and higher taxes on the rich. Gallup finds that Americans overwhelmingly think the rich pay too little:

Raising taxes on the rich enjoys broad support, including among Republicans, though this belief is not reflected at all among Republican elites:

The Quinnipiac University poll found that 60 percent of Americans among both major political parties think raising income taxes on households making more than $250,000 should be a main tenet of the government's efforts to tame the deficit. More than 70 percent, including a majority of Republicans, say those making more than $1 million should pay more.

Polling on progressive versus proportional or regressive taxes is hard to come by. The conservative Tax Foundation asked a loaded question last year: "Would you support or oppose the government redistributing wealth by a much higher income tax on high income earners?" The language seems clearly designed to prompt a negative response, but respondents said yes anyway, by a 52%-31% margin. (This is probably why the Ayers-McHenry poll cited by Brooks threw in even more loaded terms in order to produce the desired result.)

Four things you probably didn't know about the Boston Tea Party

Bruce reblogs (am I using that right?) a piece by tax historian Joseph Thorndike. It's a great read. Here enough to give you a taste:

1. The Tea Party was not a protest against high taxes. The Boston Tea Party was certainly a tax protest, but it was not a protest against high taxes. In fact, it was sparked by a tax cut, not a tax hike.

2. The Tea Party was prompted by a corporate bailout. What's not to like about cheap tea? Plenty, at least when it comes as part of a corporate bailout. Because that's what the Tea Act was: an 18th-century version of corporate welfare.

3. The Tea Party was a grass-roots movement -- with an element of AstroTurf. What moved Bostonians to activism? Ideology certainly played a role. But so did political leadership, particularly on the part of the Sons of Liberty, Adams, and Boston's merchant class.
4. The Tea Party wasn't always a touchstone of American nationalism. The Tea Party looms large in the annals of American civil disobedience. Who can't warm to the notion of outraged citizens moved to public action against monopolistic tyranny?

Well, as it turns out, quite a few people.

"Health And Virtue"

Once again we go to Chait:

This is of a piece with what, as I wrote last month, has become the dominant right-wing view of health care: that it's a matter of personal responsibility. Just as rich people are rich because they work hard (and the poor and poor because they don't), good health is largely attributable to responsible personal behavior, and poor health to sloth. Here's Jim DeMint:

In the closing chapter of “Saving Freedom,” DeMint outlines an action plant that starts with the individual. It encourages every individual to take responsibility for themselves.

“As we look at the health care of our nation, we’ve got to look at our own health care and the health care of family –– what we can do to lower the cost of health care just by taking care of ourselves.

And here's Newt Gingrich:

I think you want to re-establish that the individual has a big responsibility for their own health, because otherwise you can't deal with diabetes and obesity and things that are chronic conditions.

First Spider-Man, now Rush

You may have known that Spider-Man co-creator Steve Ditko was a dedicated objectivist. Now we learn that the Canadian band Rush was heavily and openly influenced by Ayn Rand.

Jonathan Chait has the whole story here.

How about an alternative to p-value?

Or, more accurately, a complement.

I think we can all agree that the quality of a study cannot be described by a scalar. Given that, is it possible to come up with a fairly small set of standard metrics that would give us a better picture?

P-value should be included and the set shouldn't have more than four metrics. Other than that, does anyone have any suggestions?

The ongoing tyranny of statistical significance testing in biomedical research

This is the title of an article that appears in the Europen Journal of Epidemiology. I think that it is a good contribution to the recent discussions on p-values. The authors seem to be focusing on the difference between clincial significance and statistical significance (and pointing out the many cases where the two may diverge).

Usually this is happens for strong effects with small samples sizes (real associations are hard to establish) and weak effects with very large sample sizes (where unimportant differences can be demonstrated).

I was surprised that the authors did not consider the possibility of observational meta-analysis -- which seems to me to be one of the possible ways to handle the issue of small sample sizes in any specific experiment. But I think the message is in concordance with the larger mesage that these tests are not a substitute for personal judgement. In the context of designed experiments they may be fine (as the experiment can be created to fit this criterion) but the uncritical use of p-values will also be an issue in the interpretation of observational research.

Another financial piece from This American Life

TAL provided some of (if not the) best stories to come out of the crisis and they've been on top of it since the beginning. Click here for their piece (free this week) paralleling Magnetar and Mel Brooks' The Producers.

There's also a fascinating profile of an ex-cop turned crusader against the war on drugs.