Two days ago I came across the paper, “Thimerosal exposure in infants and neurodevelopmental disorders: an assessment of computerized medical records in the Vaccine Safety Datalink,” by Heather Young, David Geier, and Mark Geier, which is listed as an Article in Press in the Journal of Neurological Sciences. This study has a lot of problems, and I predict that it will take me at least five posts to go through the article point by point to explain all the flaws. However, there’s one trick that the authors play that’s so glaring that I have to point it out immediately. In fact, I’ve spent two days in shock that the journal editor and reviewers let the authors get away with it.

Since extremely dubious “imputing” or imputation lies at the bottom of the author’s little trick, let’s back up a moment and define imputation. My mother always told me not to trust everything I read in Wikipedia, but Wikipedia does give pretty good definition of imputation: “the substitution of some value for a missing data point.” “To impute” is just the verb form of imputation. In economics and sociology, imputation is often used for the value of income. For example, a sociologist may be trying to collect data on social class. People are willing to provide information on their education, their job, and other social characterisitcs, but often they will refuse to provide info on their income. So when analyzing her data, the sociological researcher may use the person’s education, occupation, and other characteristics to impute the person’s income value. (Methods for imputation have become very complex and sophisticated. The most common are hot-deck imputation and multiple imputation.)

You may be wondering why I’ve been emphasizing the word “value.” Note that our definition of imputation is “the substitution of some value for a missing data point.” So let’s say a researcher has a file of data on children and 8% are missing data values on parent’s household income, 4% are missing data values on gestational age at birth, and 1% are missing data values on birth weight. She decides to use an imputation procedure to impute values for parental income, gestational age, and birthweight where they were missing. Perfectly fine, legitimate, and scientifically valid under most circumstances. However, let’s say the outcome she’s interested in is autism. She examines the data and sees that in certain cohorts in her study population the distribution of autism isn’t quite what she would like. So she “imputes” autism cases into the data set. Except that she’s not imputing a value on a variable for an existing study participant. She’s adding imaginary autism cases into the analysis. This isn’t imputation — it’s cooking the data. Sorry folks, but when you have a data set that comes from the real world with certain number of cases and non-cases, the data are what they are.

Let’s quote directly from the Young, Geier & Geier paper to make sure I have this right. “Because of concern that the cohorts from 1995-1996 had only 4-6 years of follow-up, frequency distributions of age at diagnosis were examined for all years. This revealed that for some of the disorders a sizable proportion of children were diagnosed after 4.5 years. Adjustments were made for counts of cases as needed for birth cohorts depending upon the disorder examined to correct for under ascertainment that occurred due to shorter follow-up times. These adjustments were made for all disorders including the control disorders as appropriate based on the age distribution….”

“For example, 37% of autism cases in the study were diagnosed after 5 years old with about 50% diagnosed after 4.5 years old. This is a conservative estimate since it includes the 2 years (1995-1996) that had shorter follow-up times. Examination of the distribution of age of diagnosis by birth year for autism revealed that only about 15% of cases were diagosed after 5 years of age in the 1995 birth cohort while the 1996 birth cohort had no cases diagnosed after 5 years of age and only 3.5% of cases diagnosed between 4.5 and 5 years of age. Based on the average age at diagnosis for all cohorts the 1995 count of autism cases was increased by 45 cases with the assumption that all of these would have been added in the 5 year+ age group (bringing this percentage close to the overall average of of 37% diagnosed after 5 years of age.) The same was done for 1996, but the number of cases was augmented by 80 because it was assumed that these would be diagnosed in the 4.5 to 5 and 5+ groups essentially bringing the percentage after age 4.5 close to the overall average of 50% diagnosed after 4.5 years of age. The new augmented frequency counts of cases in 1995 and 1996 birth cohorts were then use as new case counts in the analysis.”

This is just not done. It’s not valid. It’s not ethical. Adding imaginary cases into a data set borders on scientiific fraud. I’ve been trying to wrap my mind around some sort of rationale for the authors “imputing” extra cases and to me it’s just fudging the data. What they’ve done bears some relationship to a procedure called “direct age standardization,” but age standardardization might be useful in a situation where invesigators were comparing birth cohorts — not where the birth cohorts are the units of analysis (more on this “units of analysis” concept later). I don’t think this is downright scientific fraud for two reasons. First, they carried out this procedure of “imputing” imaginary cases for the control disorders, as well as autism and five other neurodevelopmental disorders. (I’ll explain this in more detai in upcoming posts.) Second, they come right and admit that they cooked the data by adding imaginary cases — it’s not as if they’re trying to hide anything.

Anyway, this isn’t even the biggest flaw in the paper. It just gives me the creeps that they would do such a thing. In fact, I doubt that this little trick had much effect on the rate ratios reported in Table 3. The authors do state that “sensitivity analyses revealed that point estimates were similar even when imputing [sic] 50% fewer cases than would be expected using the average age distributions as noted above.” However, as I said above, this study has a lot of problems. The “rate ratios” reported in Table 3 are surely invalid for two reasons (among others):

  • The “ecological” study design is strange, weird, and downright bizarre. It’s true that the authors could not link the separate data files, but this “ecological” design was not necessary. Instead of using a total “population at risk” of 278,624 children, the authors should have used person-time (e.g., person-months) in the denominator to calculate true rates. This is the standard approach in epidemiological studies in which there is “right censored” data, i.e. in this case, children who might eventually be diagnosed with a neurodevelopmental condition, but who had not been followed up long enough.
  • Despite appearances, from a statistical point of view this is not an analysis of 278,624 children. The “ecological” analysis actually comes down to a regression analysis of a sample size of SEVEN (7) units — the seven birth cohorts. Picture a scatter plot of 7 points were the X axis is Hg dose, the Y axis is the prevalence of a given disorder, and the 7 points are where the mean Hg dose for each birth cohort intersects the prevalence for that birth cohort. Aside from the fact that a regression analysis based on an N of 7 is unstable and not robust at all, it has been known in the social sciences since 1950 and in epidemiology since about 1973 that in general, regression estimates from ecological analyses tend to be hugely magnified compared to individual-level analyses. (By individual-level analysis I simply mean the type of study where individual exposure data and individual level outcome data is used in the analysis for every study participant.)

I will be discussing these issues in much more detail in my next few posts. If you have any quesions, don’t hesitate to comment.

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73 Responses to “New Study on Thimerosal and Neurodevelopmental Disorders: I. Scientific Fraud or Just Playing with Data?”  

  1. 1 Catherina

    Thank you for that explanation, Epi Wonk. Can I add my two cents in the shape of this paper:

    in particular figure 1 of that paper:

    you can see that the age of autism diagnosis in the 14 to 17 year old bin (so the children born between 1998 and 2001) is very variable, while in the later birth cohorts, the range of age of diagnosis is much smaller and most autism diagnoses will have been made well before age 5 years. The trend to earlier diagnosis is even more pronounced in the “milder” ASD categories. If these data are correct, then the extrapolation from diagnosis dates that Young and colleagues make is wrong and the diagnoses that they see until age 4.5 in their two youngest birth cohorts is all there is.

  2. 2 TheProbe

    Your analysis is excellent, and I look forward to the next four articles. You may wind up being sybpoenaed as Kathleen Seidel was. A badge of honor.

    There is a simpler method, though. Look for the word “Geier”. As soon as you find it in the author’s list, you know that the study really reviewed fudge (all puns intended).

    Have you considered a letter, or five, to the editor of the journal? Perhaps an emial with a link to this article, and the next four?

  3. 3 Rhymes with liar

    Mr. and Dr. Geier just got Wonk-slapped. Love it. Feel free to wear a ring with a really sharp edge for the next round. I can’t wait. Great work!

  4. 4 Blake Stacey

    General question: should these criticisms be written up more formally and sent to J. Neuro. Sci. as a comment on the article? Blog posts are good, but injecting the same points into the formal publication process might also be beneficial.

  5. 5 Uncle Dave

    I am curious as to how they collected the data that identified the children
    at ages 4.5 and 5 years of age as Autistic?

    I am curious as to the formal identification of autism prior to children
    attending school.

  6. 6 Joseph

    Also, the years 1990 to 1996 were already known to be the years when thimerosal exposure increased (perhaps the only time when it has increased significantly and gradually). Clearly, the 1990-1996 cohort would be an ideal choice if you are looking for a coincidental correlation.

    If you want to evaluate prior work by these same authors, let me recommend Geier & Geier (2004). In particular, see the sequence of years in the Figure 2 X axis, specifically 1985-1990.

  7. 7 Matt

    I can’t wait for the next installments!

    They seem to be implying that all kids who got an oral polio vaccination are fully vaccinated according to the schedule for their birth cohort. Am I reading that right? All kids who did not get the OPV were rejected?

    Also, they compare their estimated prevalence to that from the CDC’s Atlanta study from 1996. First off, their is a big difference stat-to-state observed in the CDC autism counts. Second, they are comparing an urban area with a mixed urban/rural group. Autism counts vary dramatrically by urbanicity.

    They talk about “average” age of diagnosis. Isn’t the correct measure “median” age of diagnosis? They assume that the avera/median age shoud be about the same–this at a time when autism awareness was climbing dramatically. This also as school districts in California were being required to implement ABA programs, adding a significant incentive to diagnose autism. Checks of the CDDS data for this time frame show indications of large increases in autism prevelence for birth cohorts in the 1980’s. Yes, kids over 10 were being reclassified (or classified for the first time) as autistic.

    The Geiers have dug themselves a deep hole. At present, they are trying to place the blame on others.

  8. 8 EpiWonk

    @Uncle Dave: In the Vaccine Safety Datalink the outcome files are based on “passively” collected data from hospitalizations, emergency department visits, and outpatient visits within the HMOs, and the diagnoses are then coded as ICD-9 codes. There is no active effort to seek out, screen, or diagnose autism or autism spectrum disorders.

  9. 9 kristina

    Thank you for these clarifications. When I was reading (and re-reading) the article, it was precisely how the data/numbers were handled (being manipulated) that puzzled me. The values seemed indeterminate and so many assumptions were made. But I suspect that a “lay” reader might see the “adjustments” as a further sign of the study’s “strengths.”

  10. 10 Anthony

    Yep, this study has been lept upon by the usual suspects.

    Great work Epi Wonk.

  11. 11 Science Mom

    I too am looking forward to more installments and see how they compare to my own observations seeing as how incredulous I was as well. Thank you for your concise explanations. I would like to add (for now) a note about the circulating vaccines during that ’study’ period; ActHib, HibTitre, Infanrix and Comvax, all commonly used vaccines for Hib and DTaP were and are thimerosal-free. Yes Matt, their inclusion criteria were ridiculous but at least consistent with the rest of the assumptions that they made throughout.

  12. 12 DLC

    An interesting and informative article with a deserved take-down of the scummy father-and-son team.
    Being no epidemiologist I make the comparison to a plumber or lawyer adding imaginary work hours to the bill. If such a person did something like that, they’d wind up getting their license pulled and probably be jailed for fraud. So, I consider the Geier’s guilty of academic fraud. But then, this is not a new thing for them.

  13. 13 John Best

    Hey Wonk,
    Find me some cases of autism who were born before 1931. Otherwise, shut up and admit that thimerosal caused the epidemic.

  14. 14 Uncle Dave


    Thank you for taking the time to answer my question.

    Interesting. So even within the data, whether or not some of these children are indeed truly autistic or not could also be in question.

    My wifes experience as a Sp Ed teacher for grades 1 through 3 is that many pre-school programs (southern California) lack properly trained diagnostic personnel even within the K-12 grades at many schools for that matter.

  15. 15 EpiWonk

    @John Best: I’ll send you by e-mail a copy of Dr. Sula Wolff’s article, “The history of autism,” which was published in European Child and Adolescent Psychiatry in 2004. She mentions several cases of autism born before 1931.

  16. 16 NM

    I too am an EpiWonk. However I’m at the other end of the 30 year spectrum. I think I’m going to enjoy this place. Thanks for starting it up.

  17. 17 Matt

    Wow, you got John Best to show up! I bet he followed Orac or Kev’s blogs to here. He loves those.

    John, ask CDDS for a copy of their datafiles. They were generated for a ‘private citizen’ already so they are free. They show a number of autistics in the system born before 1933.

    Then again, you’ve read me state that in a number of places already.

    But, if that is all you need to disprove your theory, it is toast. So toast that even the petitioners’ lawyers for the Omnibus gave up on it.

    Not that I expect facts to convince you. They haven’t so far.

  18. 18 Mary

    Uncle Dave, in general, rest assured that new diagnostic tools will soon resolve these issues of diagnosing the pre-schoolers.

    Wetherby and others think it may be possible to diagnose children even earlier on, perhaps before classic symptoms develop. In a study of 5385 children, she has shown that communication screening can be used as early as 9 months old to catch children who will develop autism…
    Zwaigenbaum presented research at the International Meeting for Autism Research (IMFAR) in London suggesting that rapid head growth might be detectable in children at high risk of autism who are as young as 6 to 12 months old.
    Being able to identify children at high risk of autism and offer therapy at this age would have big implications. Before 12 months, the human brain is still so flexible that it might be possible to influence it to the extent that some children don’t develop autism at all.

    I, for one, look forward to the time when it is possible to use foetal imaging to determine that the unborn isn’t smiling enough and that that must raise an ‘at risk’ flag. Surely some entrepreneur shall then persuade the parents to undertake a costly behavioural programme and then announce:
    i) the programme prevented your child from developing autism
    ii) your child is elsewhere on the ASD than s/he would have been, were it not for this intervention.

  19. 19 John Best

    Thanks for the obsolete junk. It shows you have no clue what’s going on with autism. None of those people were autistic. The author hadn’t even learned that autism is mercury poisoning 5 years after Verstraeten told us.
    And Matt, according to your warped beliefs, CDDS should have had autistics at the rate of 1 in 150 for all time not just a handful of folks born between 1931 and 1933. Since you claim they had some before 1933, not 1931, I have to assume you also can’t find any before 1931.
    A few weirdos throughout history is no case for autism. None of them report feces smearing or self abuse or being so spaced out that they would have walked in front of a charging horse. Sorry, your historical weirdos don’t fit with autism.

  20. 20 bones

    Ladies and Gentlemen, John Best!!!! (a/k/a Mr. Ignorant)

    Wow..congrats Epi Wonk!! You know you’ve hit the motherload when Best makes an appearance. You’ll have to excuse his rudeness as he tends to get a little cranky when his foot’s in his mouth.

  21. 21 Uncle Dave

    Mr. Best;
    “It shows you have no clue what’s going on with autism.”

    You don’t need to know anything about autism
    to see what is being presented here. Thats the
    whole point.

    If the subject were Brown bears with bad teeth it would still be
    the same conclusion.

  22. 22 John Best

    Yup, I’m so ignorant, my kid’s getting better because I don’t listen to jerks who play games with stat’s.
    Autism’s real simple. Inject mercury to cause it. Remove the mercury to cure it. Any questions?

  23. 23 qchan63

    May i propose that no one bother replying to Mr. Best any longer? I’d wager that his hateful rants have not come close to changing a single mind on this topic (even most people who believe vaccines=autism don’t want to be associated with him). So why bother countering his statements? With no one to string him along, he doesn’t exist.

  24. 24 alyric

    Hi Mary

    I know you’re quoting from New Scientist but this is the great canard of the decade:


    No proof at all of this mythical flexibility, though there’s plenty of proof that ABA isn’t necessarily good therapy for all two year olds (Howard et al). This early intervention notion, though pervasive rests on hot air, popular though it is with the marketers of interventions.

  25. 25 John Best

    Hundreds of people have cured their kids from reading what I’ve had to say. Where’s the hate there, simpleton? Where’s the rant? Nope, just solid information that helps kids. Too bad you and your mentally challenged associates can’t say the same.

  26. 26 trrll

    If you look at clinical trials of drugs for autism, you will find just about any darn thing, even a sugar pill, will make autistic kids get better. Back in the late ’90’s, somebody reported that some autistic kids were “cured” after receiving an injection of a gastrointestinal peptide called secretin. Thousands of kids were injected with this stuff, and there were many, many testimonials from parents about how secretin had cured their kids, and even case studies reported in the medical literature. Finally, there was a randomized, double blind, controlled study in which a bunch of autism kids were injected with secretin, and another group received injections of a salt water placebo. Sure enough, the kids who got secretin got better. So did the ones who got salt water. In fact, just as many as those who got the secretin. People couldn’t believe it! They did the study over and over again. Multiple doses. Secretin ointment. Sophisticated statistical stratification to see if maybe there was some subgroup–kids with regression, kids with gastrointestinal problems–that improved with secretin. As a result, we probably no more about secretin than any other drug treatment for autism. Every study gave the same result–secretin was no better than placebo. Fortunately, secretin seems to have been essentially harmless. It didn’t help, but it didn’t hurt either. Which is more than can be said for some modern treatment crazes such as chelation for imagined “mercury poisoning,” which can make kids sick or even kill them.

    Pretty much every clinical study of autism has showed the same thing. A large proportion, frequently over a third, of autistic kids get better after any treatment whatsoever, even placebo. Why? Some of it is probably power of suggestion. Parents of autistic kids are highly motivated to believe that something that they have done has “cured,” or at least helped, their kids. But it is also true that autism frequently gets better over time, and whatever treatment the parents have tried gets the credit.

    So I’m sure that there are indeed hundreds of people who believe that they’ve cured their kids by following John Best’s recommendation, even though in reality they have been subjecting their kids to dangerous, expensive treatments that endangered their lives, and did them no good at all. The kids got better on their own, and Best is taking the credit.

    As the evidence has continued to mount that autism has nothing at all to do with mercury, and that chelation is dangerous and useless, Best has started to sound more and more desperate. He haunts the autism blogs and spends his days insulting those who doubt the mercury-autism connection, which nowadays is pretty much the entire medical community. His comments have gotten nastier and nastier, and it is tempting to retaliate, but I doubt if there is anything that we could say that would add to his obvious torment. It is quite evident that somewhere, deep down, he is beginning to realize that he has been personally responsible for harm to untold numbers of autistic children.

  27. 27 Dr. T

    What John Best and the other fanatics about thimerisol-containing vaccines do not understand is basic toxicology. The amount of mercury in vaccines (even the older vaccines with higher concentrations of thimerisol) is tiny. Our bodies, even baby bodies, can handle trace amounts of mercury with no problems. The amount of mercury required to cause permanent brain damage is massive, and that amount of mercury would cause toxicity throughout the body, with kidney toxicity being worse. Since kidney disease is not associated with autism, it is very improbable that thimerisol is associated with autism.

    Saying that lack of autism prior to the use of thimerisol-containing injections proves that mercury causes autism is idiocy. You could just as easily blame the replacement of horses with cars as the cause of autism. People with autism 100 years ago were given other crude diagnostic labels (retarded or ‘tetched’ or insane). No one was diagnosed with tuberculosis 100 years ago. Does that mean that tuberculosis did not exist until the modern age? No, it just means that inadequate diagnostic techniques resulted in diagnoses of “consumption” which included what we now call tuberculosis and an assortment of other diseases.

  28. 28 Orac


    Got any evidence to back up that assertion, John?

    Didn’t think so.

  29. 29 daedalus2u

    What is quite ironic in John Best’s clamor for autism cases in the 1930’s is that the mercury exposure in children then was orders of magnitude higher than it ever was from thimerosal.

    During the first half of the 20th century there was the custom of using mercury containing OTC drugs for lots of different things. One of them was teething powders. The popular brands often contained a grain of calomel per dose. That is 65 mg of HgCl per dose. That is 55 mg of mercury per dose

    Many millions of doses were sold per year (30 million doses in one year by one manufacturer). The amount of mercury in a single vaccination is only about 15 micrograms. Thus many millions of children each received many thousands of times more mercury from teething powder than any child ever received from any vaccine.

    Over a thousand children died from what was called pink disease. We now know that pink disease was mercury poisoning. If autism were caused by mercury poisoning, the first half of the 20th century would have had an enormous incidence of autism.

  30. 30 John Best

    Dr T,
    Again, there was no autism 100 years ago. Nobody injected horses or cars into babies who had no blood brain barrier so your analogy is invalid. They did start injecting mercury into infants with no BBB, however, in 1991. Then the largest increase ever seen in autism happened 3 years later in 1994.
    It was not a matter of simply giving autism a name in 1943. The guy who named it said it had never been seen before. That means it did not exist. It was a new form of mental illness, clearly and distinctly different from schizophrenia, retardation and behaving like a neurodiverse nitwit.

    I have emails, some phone numbers and some addresses. Do you think I would give that information to you so your band of goons can go hunting for some dirt to begin character assassination on those parents? Those parents are happy to present their cured kids to reasonable and decent people, not to anonymous nitwits who call them liars.

    The teething powder killing kids fits right in with SIDS. I guess those kids probably had the APO-E4 protein and died before their brains were damaged into autism.
    Your placebo stuff aside, explain how chelation cured my kids constipation that he suffered with for about 5 years within 2 months of starting chelation. At that point, he was still a vegetable mentally and had no clue what the drugs we were giving him were. There could not have been any placebo effect unless the ears in his intestines heard us talking about it.
    As with the guy above, the teething powder was not given to babies before they had a BBB. So, it would’ve had a tougher time gaining access to the brain while it could have destroyed other organs and given the kids horribly painful deaths.
    Will you ever stop talking garbage that destroys children’s brains?

  31. 31 Billy Bong

    You tell them John.

    Here’s an ironic quote from the methods section of the paper (ironic because so-called epi wonk claims 30 years at CDC)

    I guess things have changed since he retired.

    “2. Materials and methods
    The study protocol employed was approved by the US
    Centers for Disease Control and Prevention (CDC), the
    Institutional Review Board (IRB) of Kaiser North–West, and
    the IRB of Kaiser Northern California. The data were
    analyzed at the secure Research Data Center of the National
    Center for Health Statistics in Hyattsville, MD. The views
    expressed in this study do not necessarily reflect those of the
    US CDC or those of Kaiser Permanente.”

  32. 32 EpiWonk

    @Billy Bong: Not 30 years at the CDC. Just the last part of my career. If I’d spent 30 years at the CDC I’d have to be institutionalized for bureaucratomania. Also, note that I never worked for the National Immunization Program (NIP). The CDC is a big place; in fact, I never even knew anyone in the NIP.

  33. 33 hitmewiththepoison

    Don’t pull a hamstring backpedaling…Just exactly how long have you worked at the CDC and what department, short order cook?

  34. 34 EpiWonk

    @hitmewiththepoison: Read my ABOUT Epi Wonk: “I worked for more than 30 years as a professor in medical schools and schools of public health and as a senior epidemiologist at the CDC.” To answer part of your question, I worked at the CDC for about 15 years. I was in the Senior Biomedical Research Service; also a Branch Chief and Division Director. If I tell you which Division or even which Center, a lot of epidemiologists will immediately guess who I am. My privacy is more important than satisfying your curiosity.

  35. 35 Uncle Dave




    “This is a neurodevelopmental disorder typically appearing in the first three years of life and characterized by impairment in communication and social skills.
    In the five-plus decades since autism was first described, much has changed in the diagnosis and treatment of the syndrome. Much research is going into a better understanding of the behavioral, biological, genetic and neurological basis as well as the treatment of this syndrome and UCLA is at the forefront of some of these research efforts.”
    Taken from UCLA’s autism program.

    See UCLA’s program below. Again I am sure there are many other similar clinics
    at Universities in and around the US.

    Like any medical condition, it seems that early diagnosis (and acceptance) and treatment in the form of
    intensive educational programs seems to make a difference.

  36. 36 andrea

    Excuse me, I’m getting over yesterday’s migraine, and just want to make sure that I am understanding something here; the paper said,

    “Based on the average age at diagnosis for all cohorts the 1995 count of autism cases was increased by 45 cases with the assumption that all of these would have been added in the 5 year age group (bringing this percentage close to the overall average of of 37% diagnosed after 5 years of age.) The same was done for 1996, but the number of cases was augmented by 80 because it was assumed that these would be diagnosed in the 4.5 to 5 and 5 groups essentially bringing the percentage after age 4.5 close to the overall average of 50% diagnosed after 4.5 years of age.”

    Does this mean that Young, Geier and Geier added 45 and 80 cases that were not in the original data sets, that they MADE UP those 125 cases just to add imaginary data points to make the stats results look more like what they wanted?!


  37. 37 EpiWonk

    Yes, they did MAKE UP those 125 cases. Hard to believe. I’m trying to write Part 4 of my critique of this paper, but it’s so bad that I keep wondering whether it’s worth it. It’s like writing a serious essay on the movie Caddyshack II.

  38. 38 andrea

    But– but– how the HEYLL did this drek get published?!


  39. 39 David

    It is not necessarily true that regressing group means to predict group rates will bias up the effect. The group mean is a noisy measure of each individual’s exposure. Attenuation bias from measurement error can lead to downward-biased coefficients. If immunizations are almost universal this result is not a problem, but I have to believe there was 7 used in the current analysis. To the extent the trends show up largely among certain groups (e.g., boys), it suggests either mercury interacting with something (genetic or environmental) or that an omitted variable affects some groups more than others. Both results are interesting and important. The latter, of course, casts doubt on the authors’ interpretation.

  40. 40 Harrison



    Well, ranting is I suppose a matter of opinion, but using phrases like simpleton and mentally challenged seems to show, if not hate, then perhaps an anger control problem. As a matter of fact, if the discussion here upsets you, why are you here?

  41. 41 Ragnar Danneskjöld

    lol john best. chelation. Why spend all that money on a chelation when Kinoki foot pads are available?

    Only $19.99!!

    They too have an independent study proving they work!

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