Mathematical Thinking: Regression To The Mean

Dr. Andreas Eenfeldt is 6’7” tall – a fact I’ve managed to work into two pre-cruise roasts, as well as the speech I gave on this year’s cruise. You can always spot the man in a crowd, unless he happens to be standing amidst an NBA team.

You might expect that his brother is equally tall, or that he’ll have a son someday who’s as tall or taller. But that expectation would be wrong. His brother (an affable guy I’ve met on two cruises) is 6’3” – still tall, but four inches shorter than Andreas. That’s because Andreas is an anomaly. He’s proof of the statistical principle that given enough chances, chance happens. And what happened in his case was probably a genetic quirk that produced some extra human growth hormone.

In his book How Not To Be Wrong: The Power of Mathematical Thinking, math professor Jordan Ellenberg explains how anomalies can produce study results that are statistically significant, but nonetheless due entirely to chance. I recounted those points in a previous post.

In a later chapter, Ellenberg describes how we can fooled by the flip-side of given enough chances, chance happens: regression to the mean. After chance happens, things tend to return to normal.

Ellenberg begins the chapter (titled The Triumph of Mediocrity) by recounting the work of a professor of statistics named Horace Secrist. After examining data on hundreds of businesses in the 1920s, Secrist wrote an influential paper with a rather startling conclusion: the competitive forces of American capitalism lead to mediocrity in business. Secrist’s evidence was that when businesses produced record-high profits one year, they tended to produce average profits in subsequent years. Likewise, firms that produced record-low profits tended to show higher profits in subsequent years. Therefore, something about capitalism must produce middle-of-the-road mediocrity, Secrist concluded.

But as Ellenberg explains, what Secrist’s data demonstrates isn’t an inherent flaw in competitive capitalism, but the simple fact that anomalies tend to be followed by a regression to the mean. A business can have a bang-up year for any number of reasons: a disaster that affects the competition, a temporary surge in demand, etc. When the temporary conditions that produced the record profits go away, so do the record profits.  It’s business as usual again.  That doesn’t mean the company’s management drifted into mediocrity.

Or on the subject of height:

People drawn from the tallest segment of the population are almost certain to be taller than their genetic predisposition would suggest. They are born with good genes, but they also got a boost from the environment and chance. Their children will share their genes, but there’s no reason the external factors will once again conspire to boost their height over and above what heredity accounts for. And so on average, they’ll be taller than the average person, but not quite so tall as their beanpole parents. That’s what causes regression to the mean: not a mysterious mediocrity-loving force, but the simple workings of heredity mixed with chance.

I don’t know how Dr. Eenfeldt would feel about being called a beanpole, but you get the idea. It’s not likely that he’ll produce a son who is 6’7” or taller.

Ellenberg points out that regression to the mean is also common in sports. An NFL running back has a record-setting year, scores a huge contract as a result, then never puts up those stratospheric numbers again. Grumbling fans assume that with all those guaranteed millions in the bank, the running back lost his desire or work ethic. In fact, it’s probably just a case of regression to the mean. The running back was never going to have another season like the record-breaking one, fat contract or not.

As a personal example that doesn’t involve fat contracts or money of any kind, I saw regression to the mean during the past five days, when I played several rounds of disc golf against my buddy Jimmy Moore. Last year I kept our scores in a spreadsheet. My average at the end of that week was 6 under par on the dot.  (It’s an easy course, by the way.)

In one game yesterday, I tossed a 10 under par … four strokes better than average, and my lowest score ever when playing against Jimmy. The next game (a mere 90 minutes later), I finished just two under par … four strokes worse than average.  When I tabulated all my scores for the five days we played, my average was … wait for it … 5.8 under par. I have good games and not-so-good games, but I always seem to drift back to right around 6 under par.

So what does all this have to do with diet and health? Plenty. Here’s an example from Ellenberg:

Almost any condition in life that involves random fluctuations in time is potentially subject to the regression effect. Did you try a new apricot-and-cream-cheese diet and find you lost three pounds? Think back to the moment you decided to slim down. More than likely it was a moment at which the normal up-and-down of your weight had you at the top of your usual range, because those are the kinds of moments when you look down at the scale, or just at your midsection, and say Jeez, I’ve gotta something. But you might well have lost three pounds, apricots or no apricots, when you trended back toward your normal weight.

Okay, so maybe a loss of a few pounds that would have happened anyway fools people into continuing with a wacky diet for awhile. That’s not a big concern in my opinion. The real concern is when regression to the mean fools doctors and researchers, or gives researchers a chance to fool doctors and the public at large.

Ellenberg doesn’t get into the subject, but Chris Masterjohn did in an article from 2011. You can read the entire article if you want the details, but here’s the main point: regression to the mean can exaggerate the reported efficacy of drugs and other treatments.

Suppose researchers are screening subjects for a trial on a cholesterol-lowering drug. Part of the screening process is a lipid panel. Because of the principle that given enough chances, chance happens, some people are going to have a spike in cholesterol on the day of the screening. So they’re now labeled as people with high cholesterol and enrolled in the study. When they’re screened again later, their cholesterol is lower – which it would have been anyway because of regression to the mean. But the lower number is attributed entirely to the drug.

As Masterjohn points out, if it’s a large enough study and the subjects were properly randomized, the regression-to-the-mean effect should be roughly equal in both groups, because both groups would include equal numbers of people whose first screening occurred on a day when their cholesterol was spiking. But smaller studies and studies in which subjects weren’t carefully randomized are particularly prone to the regression-to-the-mean effect. To quote from Masterjohn’s article:

And thus we see that many published research findings are false. Some of these false findings exist because we would inevitably expect by the laws of probability for a small handful of well conducted, thoroughly reported, and appropriately interpreted studies to uncover apparent truths that are really false simply by random chance. This emphasizes the need to look at the totality of the data. Some will be false because of regression to the mean. This emphasizes the need to critically evaluate the data in each study.

The New Yorker ran an article in 2010 about the “decline effect” — the tendency of significant results reported in scientific experiments to end up less significant or even insignificant in practice or in further experiments:

All sorts of well-established, multiply confirmed findings have started to look increasingly uncertain. It’s as if our facts were losing their truth: claims that have been enshrined in textbooks are suddenly unprovable. This phenomenon doesn’t yet have an official name, but it’s occurring across a wide range of fields, from psychology to ecology. In the field of medicine, the phenomenon seems extremely widespread, affecting not only antipsychotics but also therapies ranging from cardiac stents to Vitamin E and antidepressants.

The article partly blames the usual suspects, such as data manipulation and publication bias:

John Ioannidis, an epidemiologist at Stanford University, argues that such distortions are a serious issue in biomedical research. “These exaggerations are why the decline has become so common,” he says. “It’d be really great if the initial studies gave us an accurate summary of things. But they don’t. And so what happens is we waste a lot of money treating millions of patients and doing lots of follow-up studies on other themes based on results that are misleading.”

In 2005, Ioannidis published an article in the Journal of the American Medical Association that looked at the forty-nine most cited clinical-research studies in three major medical journals. Forty-five of these studies reported positive results, suggesting that the intervention being tested was effective. Because most of these studies were randomized controlled trials—the “gold standard” of medical evidence—they tended to have a significant impact on clinical practice, and led to the spread of treatments such as hormone replacement therapy for menopausal women and daily low-dose aspirin to prevent heart attacks and strokes. Nevertheless, the data Ioannidis found were disturbing: of the thirty-four claims that had been subject to replication, forty-one per cent had either been directly contradicted or had their effect sizes significantly downgraded.

I’m sure Ioannidis is correct about the intentional distortions.  But the article also mentions apparently honest scientists who were surprised when they couldn’t reproduce their own results, using the same methods.  Makes me wonder if some of the decline effect is simply the result of regression to the mean.

Either way, the lesson is clear:  a lot of drugs are approved based on results that don’t hold up over time.  So when your doctor prescribes the latest wonder drug, keep in mind it may not be such a wonder drug after all.  As the New Yorker article says, in the field of medicine, the phenomenon [the decline effect] seems extremely widespread.

And if you’re getting ready to pick your team for a fantasy football league, I wouldn’t count on the players who had record-setting seasons in 2014 to repeat that performance.

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64 thoughts on “Mathematical Thinking: Regression To The Mean

  1. Stephen Richardson

    An interesting idea. Whenever I have a good round of golf I become momentarily convinced that I have attained a new and improved level of skill. I might even keep my scorecard as proof of my newfound mastery. The only problem is I can’t seem to replicate the findings…

    Reply
    1. Tom Naughton Post author

      It’s called “golf” because all the other four-letter words were already taken.

      That happened to me several times when I played golf regularly. Everything seemed to come together in a round and I’d shoot an 84 or 83. Ahh, I’d tell myself, it’s this new grip (or new stance, or new body turn, or whatever.). Now I’ve got it figured out. Next time out, I’d be back to shooting north of 90.

      Reply
      1. Bret

        Kudos Tom for being around 90. I am always at or above 100, even after five years on the game. It’s embarrassing, and frustrating to high hell.

        Reply
        1. Tom Naughton Post author

          Around 90 was when I played quite a bit, and also before major shoulder surgery. I haven’t played golf since we moved to Tennessee in 2009.

          Reply
  2. Bob Niland

    «given enough chances, chance happens»

    Anomalies can happen right on the first try. On the first hole of pitch&putt golf I ever played, I got a hole-in-one.

    When this happens to a statistically naive nutrition or medical investigator, they may be doomed – spending the rest of their career trying to reproduce or extend that result on the assumption that it was the discovery of a new fundamental principle.

    Ancel, is that you?

    Reply
    1. Tom Naughton

      Ancel “found” his statistically significant results largely by ignoring data he didn’t like.

      Reply
      1. Bob Niland

        «Ancel “found” his statistically significant results largely by ignoring data he didn’t like.»

        Sure, but what was the seed of his initial bias? (and that was the thrust of my rhetorical question) Did he have some early exposure to an anomalous data set or outcome, then set his cap toward collecting (or fabricating) more evidence to support this formative experience?

        The answer to that might require more historical research than is merited (or for which there is data).

        Reply
        1. Tom Naughton

          He visited the Mediterranean region shortly after WWII and was impressed with the low rate of heart disease among some people who were living on low-fat, low-meat diets at the time. He failed to recognize that they were eating diets low in animal products largely because of the war, not because it was their traditional way of eating.

          Reply
  3. Amy

    Sounds like this principle also applies to research/studies that compare low-carb diets to low-fat diets. When they run for just a few weeks or even a few months, LCHF almost always achieves better results, across *most* parameters — fat loss, A1c, trigs, blood pressure, HDL, etc. But when studies But when they revisit the subjects a year or two later, most people seem to be back where they started, which makes it look like low-carb no mo more effective than low-fat. (Because, by that time, there are no longer any [statistically] “significant” differences between the groups.) BUT…this is most commonly due to people on low-carb not actually *staying* with low-carb for the long term. Those of us who *do* make it a permanent change, know darn well LCHF is fantastically effective — especially if we have a history of (failed) low-fat and calorie-counting to compare it to.

    Studies that show low-carbers “regress to the mean” after a while tend to not advertise that this happened because they regressed to their original crappy diets.

    On another note, Tom, I saw Fat Head years ago, but have only recently started reading your blog. I’m catching up on some of your older & most popular posts. You, sir, are awesome. I love how you point to the inanity of it all. You’re hilarious, which makes all this go down a lot easier, but at the same time, the reason we have to laugh at it is because it’s all so, so tragic and ridiculous. If we didn’t laugh, the alternative is to go at the USDA, ADA, FDA, and AMA with knives and pitchforks. (And actually, now that I think about it, that doesn’t sound like a bad idea…) Thank so much for your work! The combination of your eloquent writing and your sense of humor is dynamite.

    Reply
    1. Tom Naughton

      Thank you. I believe laughing at The Anointed is good medicine.

      I checked a handful of studies like those you mentioned. Indeed, the low-carbers weren’t usually low-carbing it by the time the final comparison was made.

      Reply
  4. Kathy in Texas

    My husband will never believe that a sports figure who signs a multi-million dollar contract doesn’t think he can relax a little and (hopefully) avoid a career-ending injury. I don’t know if I agree, but I’m not going to bring it up. Peace-keeping and all that. 🙂

    On the other hand, I totally agree with the Regression to the Mean concept. If you pay attention, you’ll see it happening everywhere.

    Reply
    1. Tom Naughton

      As a Titans fan, I saw regression to the mean after Chris Johnson’s career year landed him a fat contract. Now he’s not even on the team.

      Reply
  5. Bob Niland

    «given enough chances, chance happens»

    Anomalies can happen right on the first try. On the first hole of pitch&putt golf I ever played, I got a hole-in-one.

    When this happens to a statistically naive nutrition or medical investigator, they may be doomed – spending the rest of their career trying to reproduce or extend that result on the assumption that it was the discovery of a new fundamental principle.

    Ancel, is that you?

    Reply
    1. Tom Naughton Post author

      Ancel “found” his statistically significant results largely by ignoring data he didn’t like.

      Reply
      1. Bob Niland

        «Ancel “found” his statistically significant results largely by ignoring data he didn’t like.»

        Sure, but what was the seed of his initial bias? (and that was the thrust of my rhetorical question) Did he have some early exposure to an anomalous data set or outcome, then set his cap toward collecting (or fabricating) more evidence to support this formative experience?

        The answer to that might require more historical research than is merited (or for which there is data).

        Reply
        1. Tom Naughton Post author

          He visited the Mediterranean region shortly after WWII and was impressed with the low rate of heart disease among some people who were living on low-fat, low-meat diets at the time. He failed to recognize that they were eating diets low in animal products largely because of the war, not because it was their traditional way of eating.

          Reply
  6. Amy

    Sounds like this principle also applies to research/studies that compare low-carb diets to low-fat diets. When they run for just a few weeks or even a few months, LCHF almost always achieves better results, across *most* parameters — fat loss, A1c, trigs, blood pressure, HDL, etc. But when studies But when they revisit the subjects a year or two later, most people seem to be back where they started, which makes it look like low-carb no mo more effective than low-fat. (Because, by that time, there are no longer any [statistically] “significant” differences between the groups.) BUT…this is most commonly due to people on low-carb not actually *staying* with low-carb for the long term. Those of us who *do* make it a permanent change, know darn well LCHF is fantastically effective — especially if we have a history of (failed) low-fat and calorie-counting to compare it to.

    Studies that show low-carbers “regress to the mean” after a while tend to not advertise that this happened because they regressed to their original crappy diets.

    On another note, Tom, I saw Fat Head years ago, but have only recently started reading your blog. I’m catching up on some of your older & most popular posts. You, sir, are awesome. I love how you point to the inanity of it all. You’re hilarious, which makes all this go down a lot easier, but at the same time, the reason we have to laugh at it is because it’s all so, so tragic and ridiculous. If we didn’t laugh, the alternative is to go at the USDA, ADA, FDA, and AMA with knives and pitchforks. (And actually, now that I think about it, that doesn’t sound like a bad idea…) Thank so much for your work! The combination of your eloquent writing and your sense of humor is dynamite.

    Reply
    1. Tom Naughton Post author

      Thank you. I believe laughing at The Anointed is good medicine.

      I checked a handful of studies like those you mentioned. Indeed, the low-carbers weren’t usually low-carbing it by the time the final comparison was made.

      Reply
  7. The Older Brother

    the Israeli air force decided that it was a bad idea to reward or recognize an exceptional training performance, and good to punish a bad one, because a praised great performance seemed to usually be followed by worse, whereas a criticized bad performance generally resulted in an improved next exercise. Simple regression to the mean.

    Cheers

    Reply
    1. Firebird

      They must have gotten that technique from my parents…not that it worked well on me. (And I have the psychiatric bills to prove it)

      Reply
  8. Kathy in Texas

    My husband will never believe that a sports figure who signs a multi-million dollar contract doesn’t think he can relax a little and (hopefully) avoid a career-ending injury. I don’t know if I agree, but I’m not going to bring it up. Peace-keeping and all that. 🙂

    On the other hand, I totally agree with the Regression to the Mean concept. If you pay attention, you’ll see it happening everywhere.

    Reply
    1. Tom Naughton Post author

      As a Titans fan, I saw regression to the mean after Chris Johnson’s career year landed him a fat contract. Now he’s not even on the team.

      Reply
  9. Maria J

    Thanks for another thought provoking post, Tom. And a few “out loud laughs” from the comments.

    Reply
  10. mrfreddy

    This is tangentially related to something I read about in “Thinking, Fast and Slow” (hat tip to Dr. Eades blog for recommending it), where the author talks about the law of small numbers (or something like that).

    I can’t really explain it but let me try anyway. Let’s say you have a study, or say, a big jar of hundreds of marbles with equal amounts of two colors. If you only take out small samples, for example, take out six marble at a time, there is a very good chance that you will have anomalous results (like all six marbles will be the same color). If your sample size is big enough, the results are more inline with what you’d expect, an equal number of marbles of each color.

    In other words studies involving small numbers of subjects can be extremely misleading.

    So, Dean Ornish, Dr. Esselstyn, etc., say again how many people were in those studies you tout so loudly?

    Reply
    1. Tom Naughton Post author

      Sure, that’s basic statistics. If you flip a coin three times and it comes up heads twice, you can’t conclude that a flipped coin comes up heads 2/3 of the time. You need hundreds and preferably thousands of flips to have a true outcome.

      Reply
  11. Josh

    “some people are going to have a spike in cholesterol on the day of the screening. So they’re now labeled as people with high cholesterol and enrolled in the study. When they’re screened again later, their cholesterol is lower – which it would have been anyway because of regression to the mean. But the lower number is attributed entirely to the drug.’

    OK, but would not the opposite also be true. Some people have unusually low cholesterol on the day of the screening and thus the drug would seem to be less effective at the next screening.

    I am not defending the drugs, just pointing out that there are two sides to this coin.

    Reply
    1. Tom Naughton

      That is a possibility, but if the treatment is intended to lower high cholesterol, the people with unusually low cholesterol would be excluded from the study — no high cholesterol to treat.

      Reply
  12. Josh

    “some people are going to have a spike in cholesterol on the day of the screening. So they’re now labeled as people with high cholesterol and enrolled in the study. When they’re screened again later, their cholesterol is lower – which it would have been anyway because of regression to the mean. But the lower number is attributed entirely to the drug.’

    OK, but would not the opposite also be true. Some people have unusually low cholesterol on the day of the screening and thus the drug would seem to be less effective at the next screening.

    I am not defending the drugs, just pointing out that there are two sides to this coin.

    Reply
    1. Tom Naughton Post author

      That is a possibility, but if the treatment is intended to lower high cholesterol, the people with unusually low cholesterol would be excluded from the study — no high cholesterol to treat.

      Reply
  13. Joe Dokes

    I think it’s complicated. I think science is really hard. I also think that our current system of scientific journals rewarding research with big results encourages scientists to make the biggest splash possible. As a result most results are probably optimistic to say the least.

    On the other hand, I know from personal experience that over time given the fact that reality is a cruel master the truth wins out. While we may lament the fact that LFHC diets were popular for forty years over the long run, science and the search for truth will win. I think we’ve now begun to see the results of this, fat is no longer the main evil culprit. Carbs are now considered a true source of obesity. Will it take another decade to completely undo Keys? Probably, but it will happen because the scientific method eventually reveals the truth.

    Another example is anti-depressants. Yes, they are not the wonder drug the pharmaceutical industry sold us on, but over the long term we will probably learn, the some people, with certain brain chemistry benefit immensely from these drugs. But like a lot of other things they shouldn’t be handed out like candy.

    Regards,

    Joe Dokes

    Reply
    1. Tom Naughton

      Agreed. Part of the problem with the over-prescribing of anti-depressants and other psychiatric drugs is that psychiatrists, like doctors in general, are drawn to the idea of a magic pill to treat a condition.

      Reply
  14. Joe Dokes

    I think it’s complicated. I think science is really hard. I also think that our current system of scientific journals rewarding research with big results encourages scientists to make the biggest splash possible. As a result most results are probably optimistic to say the least.

    On the other hand, I know from personal experience that over time given the fact that reality is a cruel master the truth wins out. While we may lament the fact that LFHC diets were popular for forty years over the long run, science and the search for truth will win. I think we’ve now begun to see the results of this, fat is no longer the main evil culprit. Carbs are now considered a true source of obesity. Will it take another decade to completely undo Keys? Probably, but it will happen because the scientific method eventually reveals the truth.

    Another example is anti-depressants. Yes, they are not the wonder drug the pharmaceutical industry sold us on, but over the long term we will probably learn, the some people, with certain brain chemistry benefit immensely from these drugs. But like a lot of other things they shouldn’t be handed out like candy.

    Regards,

    Joe Dokes

    Reply
    1. Tom Naughton Post author

      Agreed. Part of the problem with the over-prescribing of anti-depressants and other psychiatric drugs is that psychiatrists, like doctors in general, are drawn to the idea of a magic pill to treat a condition.

      Reply
    2. Josh

      Maybe Tom, but suppose my cholesterol is normally 270, but on the day they measure, for some unknown reason it is only 225. I take the statin (Lucky Me!) for three months and get re-tested. My cholesterol now measures 230. The conclusion might be that the statin did not do much, but in reality it has knocked 40 points of my average cholesterol. The statin did its job well, whether or not that benefits me is another issue.

      Again, I am not defending statins or the fixation on one cholesterol number. Just saying that we need to be vigilant and not make the same mistakes made by those who would have us all eating non-fat this, high-carb that and taking drugs even though we are not sick.

      Reply
      1. Tom Naughton Post author

        Sure, that could happen, but keep in mind it’s a drug designed to treat high cholesterol, so only people with high cholesterol will be enrolled. So given a specific cutoff number — say, 230 total cholesterol — we’ll have a cluster of people who were pushed above it or below it by anomalous readings. Everyone above will enrolled, everyone below will be excluded. Your example — guy whose normal reading is 270 but is screened at 225 — would be excluded. The guy whose normal reading is 215 but spiked at 235 will be enrolled.

        Yes, your example guy could have had an unusually low reading of 235 and been enrolled, but at any given cutoff number, we would (in theory) have equal numbers of people who come in above or below only because of the anomalous reading. That will load the study with more people whose readings were artificially high than artificially low.

        Reply
        1. Firebird

          My cholesterol was 330 at last check up. I started taking lecithin and niacinamide from the Vitamin Shoppe. My cholesterol dropped 30 points in one month. I didn’t tell my doctor I had done this. Even though it dropped 30 points, the doc said it wasn’t a significant drop…10% in one month? He wasn’t impressed when I told him I was using lecithin and niacinamide. Had that been a statin, he’d be thrilled!

          When he offered an Rx for statins and I said no, he countered with…get this…and Rx for timed release N-I-A-C-I-N.

          Head. Bang. On. Desk. (or in this case, examination table.)

          Reply
    3. Josh

      The temptation to treat otherwise healthy people in order to keep them healthy is huge. Especially, when there is a lot of profit in it.

      We did it successfully with infectious diseases like polio. But, they often only required one dose or, maybe, an occasional renewal dose every 10 years or so. They were not day after day after day dosages such as with statins and antidepressant. The daily dosing of healthy people must be a real financial temptation.

      Reply
        1. Walter Bushell

          Not only the statins themselves and monitoring them, but to treat the side effects and, of curse, drugs to treat the side effects of those drugs and so repeat ad infinitum or the patient dies. People have been known to recover when sent to hospice and taken off their drugs.

          Saturday Night Live did a spoof on this about what 35 years ago.

          Reply
          1. Tom Naughton Post author

            Wish I could remember where I read or heard about this: some guy was told he was going to die soon, nothing could be done. So he stopped taking all his drugs … and made a full recovery from the supposed disease.

            Reply
            1. Esther

              My husband was killed by the treatment the doctors devised to break up a blood clot in his portal vein so I can well believe this.

      1. Firebird

        My doctor wanted to put me on a statin because my cholesterol was high. He said it was to prevent heart disease. I asked him for insulin in case I get diabetes and chemo in case I get cancer. He shut up.

        Ironically he left his practice to set up a fat loss clinic. Replacement bars, replacement meals, replacement shakes, Cool sculpting and stomach staples.

        Reply
        1. Paula

          “My doctor wanted to put me on a statin because my cholesterol was high. He said it was to prevent heart disease. I asked him for insulin in case I get diabetes and chemo in case I get cancer.” This struck me as the most brilliant response to statin-pushing that I’ve yet seen. I absolutely plan to use this if necessary. My TC was last clocked at 254, but I now get all my testing done at a walk-in clinic for the express purpose of avoiding a doctor’s knee-jerk reaction to that number…which includes nice, high HDL and lovely, low trigs…so my doctor actually has no idea of my numbers. Since going LCHF I haven’t actually needed to see him for years.

          Reply
  15. Linda

    Well, I’ve been reading comments avidly, as I always do, and the last couple do resonate. As I’ve said before, I take care of my 95 year old father under the VA system. He has been gradually fading and getting worse and worse. They have supplied a hospital bed, home aides, etc. and his doc had prescribed a bucket load of prescriptions. Just two weeks ago, I persuaded his doc to refer him to Hospice, because we can no longer even get him to appointments, etc. Well, the Hospice doc took him off of all eight scripts (including the statin,) except one mild old stand-by for indigestion. He has started eating again, and I’ll swear, he’s looking better. His constant diarrhea has stopped and he’s talking and reading his daily newspaper again. He may not live long, but saving him from the VA doc has improved his quality of life! Who knows though? His mom lived to 101 and never took anything- didn’t believe in it.

    Reply
  16. Linda

    Well, I’ve been reading comments avidly, as I always do, and the last couple do resonate. As I’ve said before, I take care of my 95 year old father under the VA system. He has been gradually fading and getting worse and worse. They have supplied a hospital bed, home aides, etc. and his doc had prescribed a bucket load of prescriptions. Just two weeks ago, I persuaded his doc to refer him to Hospice, because we can no longer even get him to appointments, etc. Well, the Hospice doc took him off of all eight scripts (including the statin,) except one mild old stand-by for indigestion. He has started eating again, and I’ll swear, he’s looking better. His constant diarrhea has stopped and he’s talking and reading his daily newspaper again. He may not live long, but saving him from the VA doc has improved his quality of life! Who knows though? His mom lived to 101 and never took anything- didn’t believe in it.

    Reply
  17. Jonah

    The New Yorker obviously does not employ statisticians, nor drug companies, apparently, who can recognize possibilities for type i errors, or at least let us know how confident they are in their “random” samples. Basic Statistics: Type I and II errors

    Reply
  18. Jonah

    The New Yorker obviously does not employ statisticians, nor drug companies, apparently, who can recognize possibilities for type i errors, or at least let us know how confident they are in their “random” samples. Basic Statistics: Type I and II errors

    Reply

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