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I’ve been following the development of the BGI study on IQ pretty closely. I wanted to note two main caveats people should be aware of with regard to its methodology.

First, as with any case-control study, volunteer bias will be an issue. If the cases are a certain class of very smart people, rather than a representative sample, then genes peculiar to that class of smart people will show up as hits. The BGI study is choosing people who are more math than verbal-oriented; will math-specific genes show up as general intelligence genes? Other confounds along these lines are possible– PhD genes, Ashkenazi genes, curiosity in new study genes, etc..

Second, because the study doesn’t completely control for family environments (possible only by comparing siblings to each other), gene-environment correlations and interactions can cause problems as well. For example, suppose that high IQ parents also confer better environments for their children. Then the IQ gene effects will get an extra “boost” from that environment.

None of this is to downgrade the awesomeness of the BGI study. It should be viewed as an important step in resolving the nature vs nurture controversy. Overeager journalists and bloggers are urged to wait a few more years before we finally resolve the IQ debate.

(Republished from GNXP.com by permission of author or representative)
 
• Category: Science • Tags: Genomics 
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A while back, Mark and I were working on a comprehensive post which would try to tally the results of the various IQ-gene studies to see what they said about racial differences. We began this quest bright-eyed and hopeful that we would help contribute to ending a calamitous debate that has gone on for way too long. However, as we learned more about genetics, and these studies in particular, we came to realize that it’s too early to take IQ-genes seriously.

We began with an approach similar to what Half Sigma did 2 years ago with the DTNBP1 gene. However, we soon learned that this approach was incredibly flawed and misleading. I wasn’t going to write this post, but recently Half Sigma’s DTBP1 post was linked from Reddit and tens of thousands of people are viewing it. When I saw that, I frustratedly criticized HS. He responded that I should give a more diplomatic and reasoned response, so here it is:

  1. You cannot simply add up SNPs from the same gene or chromosome. Half Sigma simply adds the observed effects of the SNPs to one another, ignoring that the alleles are highly correlated with one another, and not independently inherited, which is referred to as linkage disequilibrium (LD). The study that Half Sigma used provides the following table of LD for its SNPs:

    rs2619539 rs3213207 rs1011313 rs2619528 rs760761 rs2619522 rs2619538
    rs2619539 - 0.156 0.111 0.0 0.0 0.001 0.055
    rs3213207 1.0 - 0.014 0.334 0.403 0.34 0.076
    rs1011313 0.916 1.0 - 0.037 0.033 0.036 0.081
    rs2619528 0.024 0.955 1.0 - 0.838 0.737 0.128
    rs760761 0.015 1 1.0 0.96 - 0.854 0.166
    rs2619522 0.04 0.955 1.0 0.867 0.96 - 0.182
    rs2619538 0.242 0.823 0.825 0.648 0.772 0.778 -

    As can be seen in this table, pairwise LD goes as high as 1.0, meaning that two of the alleles are always inherited together. Adding these SNP’s together is therefore like counting them twice.

  2. Group comparisons require replication in both groups. Because different populations have systematic genetic and environmental differences, an effect in one group may not occur in another. The study that Half Sigma uses relies primarily on a (small) sample of Dutch people. It is unclear whether these effects would exist in a population of African ancestry, let alone another European one.
  3. Candidate-gene association studies are not reliable. This is the most important point. Candidate gene association studies have largely failed to replicate. In fact, there have been no common IQ polymorphisms which have been replicated. Genome-wide association studies, which don’t suffer as severely the various biases of candidate-gene association studies like publication bias or the winner’s curse have not shown common SNP-associations with IQ.

    IQ is highly heritable, so the problem is the current methods, not the search for genes. With the development of sequencing technology and huge cohorts, we will be able to see the genes that are really behind normal IQ variation. With replication in multiple ethnicities and races, we will also see to what extent various genes and environments are responsible for group differences. There’s no need to make proclamations of victory for hereditarianism or environmentalism in the mean time.

(Republished from GNXP.com by permission of author or representative)
 
• Category: Science • Tags: Behavior Genetics, IQ 
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Because so many people abuse or misunderstand the concept of heritability, I decided that it would be nice to have a list of what heritability is not in one place. If you have questions or if there is a misconception about heritability you’d like me to address here, feel free to comment. This post will serve as an updated reference.


  • Heritability is not an indicator of malleability. Entirely genetic disorders such as phenylketonuria can be cured through the proper diet.
  • Heritability is not a measure of straightforward genetic effects. For example, genes that affect physical appearance have an effect on personality development.
  • Heritability is not independent of the population. It may differ from one group of individuals to the next, because groups differ environmentally and genetically.
  • Heritability is not independent of age. The effects of genes or environments may grow in potency through development.
  • Heritability is not an indicator of the causes of group differences. A trait can be highly heritable, as in the crop field metaphor, and group differences may still be due to environment. This applies also in the real world situation for humans, where the environmental differences between groups are not as systematic.
  • Heritability is not necessarily homogeneous within a population. A heritability of 50% may be hiding the heritabilities of 40% and 60% in subgroups.
  • Heritability is not a measure of intergenerational transmission. A trait may be highly heritable but not pass on from one generation to the next. This is because the relevant genes and environments may differ from one generation to the next.
  • Heritability is not a statistic for individuals. If you are using your knowledge of heritability to understand a single individual you are a biographer, not a scientist.

So, some of you may be wondering, why is heritability a useful statistic? That’s easy to answer: it’s a measure of how much phenotypic variation in a given population at a given time is due to genetic variation in that population. Measuring heritability allows us to say that, for adults in the modern world, variation on IQ and personality measures is primarily due to genetic variation. That’s a pretty remarkable, and important finding if you ask me.

(Republished from GNXP.com by permission of author or representative)
 
• Category: Science • Tags: Genetics 
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A frequent claim in the IQ debates is that which family you are raised in has no lasting impact on your IQ. Jensen argues in The g Factor that the only causes of IQ similarities between adult identical twins are genetic. Many researchers go so far as to argue that by 12 years of age, the shared environment has no impact.

Based on my limited knowledge of the behavior genetic research, I used to hold this position as well. But thanks to some recent in depth reading, I have come to the conclusion that which family you are raised in matters significantly for your IQ as an adult, especially so for people of lower socioeconomic status. I’ll detail the behavior genetic evidence here, and argue that it points to significant shared environmental influences on adult IQ scores.

Twin Studies

The most recent and comprehensive survey of twin studies on IQ comes from Haworth et al (2009). Using pooled twin data from around the world, they modeled genetic and environmental influences as a function of age. Here is what they found regarding the effects of the shared environment:

[S]hared environment shows a decrease from childhood (33%) to adolescence (18%) but remained at that modest level in young adulthood (16%).

In an email exchange with Dr. McGue (one of the co-authors of the paper) he told me that while the latest data may not fit with earlier estimates, it’s actually more reliable due to the unprecedented sample size (11,000 pairs of twins).

One failing of this study, though, is that it doesn’t go far enough into adulthood. The young adult group ranges from 14 to 34 years of age, with an average age of 17. In contrast, McGue (1993) looked seperately at data on adults over 20 years of age. He found that the shared environment diminished to zero impact at that point. Here’s his chart:
Looking at that chart, you might quickly conclude that shared environmental influence evaporates by age 20. However, this conclusion is premature. Twin studies make a great number of assumptions, some of which increase and others of which decrease estimates of the shared environment. A straightforward way of bypassing these assumptions is to compare monozygotic twins reared apart (MZAs) to monozygotic twins reared together (MZTs). The following data comes from a comparison of MZTs and MZAs, of average age 41, in Bouchard (1990):

Measure MZA correlation MZT correlation
WAIS IQ-Full Scale 0.69 0.88
WAIS IQ-Verbal 0.64 0.88
WAIS IQ-Performance 0.71 0.79

Differences between MZA’s and MZT’s on Raven’s Progressive Matrices follow the same pattern but are even more extreme. Bouchard (1981) reported a median correlation of only 0.58 for adult MZA’s on the Raven’s. Curiously, though, MZA’s are equally if not more correlated than MZT’s on the Mill-Hill vocabulary test. Apparently, the pattern is that more g-loaded tests tend to show stronger evidence of lasting shared environmental impact.

It’s worth noting that MZT vs. MZA comparisons are actually biased towards an underestimation of shared environmental impact. Bouchard’s study of twins reared apart found an environmental correlation of .22 for MZAs on various environmental measures, with some having a small but significant correlation with IQ scores. Also MZA’s share the womb. To summarize: when the assumptions of the twin method are effectively controlled for, lasting shared environmental impacts are revealed.

Adoption Studies

To date, most adoption studies of IQ have concluded that being adopted by a new and typically well-off family has no effect on adult IQ scores. Here is a chart of adoption studies from Bouchard (2009):As you can see by clicking it, the IQ correlation between unrelated individuals in the same family decreases (on average) from .26 in childhood to .04 in adulthood (which begins at age 17 for the purposes of this graph).

However, as with the previous chart, the quick conclusion that shared environmental influences don’t matter in adulthood shouldn’t be so quickly accepted. To begin with, we can see that the adoption data underestimates the shared environment relative to the twin literature. This most likely occurs because of the assumptions that go into adoption studies.

Stoolmiller (1999), for example, highlighted the issue of range restriction– the idea that the limited range of adoptee and adoptive family environments will lower estimates of the shared environment. This idea is supported by studies which make the extra effort to include individuals of lower SES. The French adoption studies that made such an effort buck the trendline seen above, in finding that nurture matters almost as much as nature for the IQ of 14 year olds. Scarr (1993) is the outlier in the adoption graph above, finding a .19 correlation between unrelated adolescent siblings. Perhaps her results differed from others because her sample was multi-racial and therefore less range restricted. Lastly, there are other lines of evidence supporting the idea of range restriction, such as Turkheimer’s work on SES and cognitive ability.

It’s worth noting, however, that McGue (2007) looked for evidence of range restriction effects within the “broad middle class” and did not find any. He used statistical methods that are over my head to estimate the effects of range restriction based on a range restricted sample and state census data. Unfortunately there are no studies which have critiqued his as of yet. Any commenters who are familiar with the statistics involved are invited to comment. Even if McGue is right about restriction of range, my point stands that assumptions inherent in the adoption studies deflate c^2 estimates.

Future Directions

Future work will help sort out the still unanswered question of shared environmental influences on adult IQ scores. There are large longitudinal adoption studies currently under way, and I believe that Haworth’s twin study will be followed-up on and include data on older twins. There are also interesting (albeit less methodologically agreed upon) studies coming out like this one, which find significant shared effects on IQ in adulthood.

My reading of the available evidence is that there is a significant shared environmental input to adult IQ, and that it is associated with socioeconomic status. To what extent it’s the neighborhood or the parents themselves that matters is unclear. Just as the most g-loaded tests show the most shared environmental effects in the MZA-MZT comparison, so too does the Flyn
n effect occur on the most g-loaded tests, suggesting that whatever is loading onto the “shared environment” within generations is also responsible for differences between them.

(Republished from GNXP.com by permission of author or representative)
 
• Category: Science • Tags: Behavior Genetics, IQ 
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In researching for a review of The Nurture Assumption, I read over the debate between Harris and Sulloway over birth order effects on personality. Sulloway’s thesis, explained in Born to Rebel, is that last-born children have more rebellious, agreeable, and open-minded/liberal personalities, and that this manifests itself in history with revolutions spearheaded by last-borns. This runs in contrast to Harris’s theory that the family environment has no lasting impact on personality, so she spends a good deal of time in her books and articles critiquing it.

The whole debate makes my head dizzy. A seemingly simple empirical question has produced years of arguing over methodology. I’m not going to go over the tedious back and forth here, except to say that you can see what both sides have to say with a Google search.

Large, controlled studies have not been kind to Sulloway’s thesis. http://www.ssc.wisc.edu/wlsresearch/pilot/P01-R01_info/aging_mind/Aging_AppA8_Freese_etal_ASR1999.pdf">Freese, Powell, and Steelman (1999) looked for a relationship between birth order (controlled for family size) and a variety of political measures on the nationally representative General Social Survey (GSS). They found no significant associations, contrary to Sulloway’s predictions.

I decided to look at the GSS myself, this time to see whether questions that tapped into personality characteristics outside of politics showed any relationship with birth order (SIBORDER), when sibship size (SIBS) was controlled for. I excluded only children. I used the Multiple Regressions feature on the Berkeley SDA tool. I found no significant associations between birth order and any of the four variables I looked at:

  • MEMLIT (proxy for openness/creativity)- “Here is a list of various organizations. Could you tell me whether or not you are a member of each type? m. Literary, art, discussion or study groups”
  • TRUST (proxy for agreeableness) – “Generally speaking, would you say that most people can be trusted or that you can’t be too careful in life?”
  • WORLD4 (proxy for agreeableness) – “People have different images of the world and human nature. We’d like to know the kinds of images you have. Here is a card with sets of contrasting images. On a scale of 1-7 where would you place your image of the world and human nature between the two contrasting images? 1. Human nature is basically good. 7. Human nature is fundamentally perverse and corrupt.”
  • OBEYLAW (proxy for rebelliousness) – “In general, would you say that people should obey the law without exception, or are there exceptional occasions on which people should follow their consciences even if it means breaking the law?”

I wouldn’t say that we should write off the idea of birth order influences on personality and intelligence, only that we should be very skeptical of them. To the extent that they do exist, they’re probably not very significant.

(Republished from GNXP.com by permission of author or representative)
 
• Category: Science • Tags: Psychology 
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A family member just sent me this New York Times article on the recent failure to replicate a serotonin gene associated with depression in a meta-analysis by Risch and Merikangas. It gives a pretty good overview, but I think the article might be misleading in two ways:

First, beginning with the title “Report on Gene for Depression Is Now Faulted” will confuse people into thinking that the genetics behind depression will be simple, when in fact the reigning theory is that large numbers of genetic (and environmental) variants influence such complex mental traits.

Second, the critics of depression genetics make misleading points:

By contrast, she said, a major stressful event, like divorce, in itself raised the risk of depression by 40 percent.

Stressful life events are themselves quite heritable.

(Republished from GNXP.com by permission of author or representative)
 
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A study from Wicherts et al published online in the journal Intelligence today:

On the basis of several reviews of the literature, Lynn… concluded that the average IQ of the Black population of sub-Saharan Africa lies below 70. In this paper, the authors systematically review published empirical data on the performance of Africans on the following IQ tests: Draw-A-Man (DAM) test, Kaufman-Assessment Battery for Children (K-ABC), the Wechsler scales (WAIS & WISC), and several other IQ tests (but not the Raven’s tests)… Results show that average IQ of Africans on these tests is approximately 82 when compared to UK norms.

UPDATE: Tables and Figures below the fold

Table 4. Results by subsets of samples.

Table 5. Estimates of mean IQs per country on the basis of studies in Table 2 and studies from the Raven’s study.

Fig. 1. Scatterplot of data from study by Lynn (2006) and Lynn and Vanhanen (2006).

Fig. 2. Scatterplot of data from study by Rindermann (2007).

Fig. 3. Scatterplot of data from study by Lynn and Mikk (2007).

Fig. 4. Scatterplot of data from study by Lynn et al. (2007).

Fig. 5. Mean of samples that meet our inclusion criteria against the inverse of the standard error.

Fig. 6. Mean of samples from studies published prior to 2006 against the inverse of the standard error.

(Republished from GNXP.com by permission of author or representative)
 
• Category: Science • Tags: IQ 
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Price of “Ahmadinejad to Win Iranian Election” on Intrade:

(Republished from GNXP.com by permission of author or representative)
 
• Category: Science • Tags: Politics 
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Compare monochorionic to dichorionic twins. If there’s a teratogen causing homosexuality then it should show up as a statistical difference in concordance for homosexuality.

Of course this would only tell us whether there is a prenatal pathogen. It wouldn’t rule out the possibility that there is a pathogen that only strikes later on.

(Republished from GNXP.com by permission of author or representative)
 
• Category: Science • Tags: Behavior Genetics 
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Check out Mark Wethman’s new quant blog, Congenial Times. It’s been around for only a couple of weeks but in that time he’s posted a lot of interesting data/analysis on topics ranging from international politics to human biodiversity. His most recent post is on racial differences in educational attainment in Sweden.

The most interesting article to me has been the one on Amish IQ scores. He found data which showed the Amish to have above average reasoning and quantitative analysis skills.* Data like this is essential for anyone trying to understand the Flynn Effect or between-population differences on IQ scores.

*They scored lower on language tests, but according to Jason Malloy this was solely due to the tests not being in their native Pennsylvania Dutch.

(Republished from GNXP.com by permission of author or representative)
 
• Category: Science 
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In a recent post, Agnostic dismissed Jean Twenge’s thesis that narcissism has increased over the last couple of decades. Twenge has been on my reading list for a while, so this intrigued me. Not feeling knowledgeable enough to play devil’s advocate against agnostic, I sent Professor Twenge an email inviting her to join the thread. She does a pretty good job of defending her thesis against agnostic’s criticisms, in my opinion. I invite anyone who’s interested to check out the thread, read the studies, and share their own two cents.

(Republished from GNXP.com by permission of author or representative)
 
• Category: Science • Tags: Personality 
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(Republished from GNXP.com by permission of author or representative)
 
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Jim Manzi writes that it’s plausible that epistatic interactions are central to complex mental phenotypes, and that they might therefore prevent genome-wide association studies from achieving much success. In the comments to a response post by Razib, Jason Malloy does a pretty good job of showing that traits like IQ are primarily additive and that epistasis therefore won’t prevent successful GWA with good sample sizes. [UPDATE 06-25-2009: I've read more behavior genetics, and I'm not quite sure that Jason's view is correct. I think it's still an open question, actually.]

With all that in mind, some epistasis does exist, and it is worth uncovering. It will not be uncovered directly by genome-wide searches, though, because of multiple testing issues. Even a two-dimensional search overwhelms foreseeable sample sizes. However, a multi-step approach could work by breaking down the multiple dimensions into individual searches. Say that gene-A and gene-B only have an effect when they appear together. Thus, a GWA should pickup an effect from either gene-A or gene-B (whichever has a higher minor allele frequency, presumably), even if that effect is smaller than the overall effect of having both of them. Now, suppose we identify via GWA that gene-A is contributing to the phenotype. We could then do a second scan for interactions and identify gene-B.

Of course, scientists are not limited solely to association searches. They can also harness biological evidence of epistasis to help identify candidates. Because traits like IQ are primarily additive, epistasis is not the overwhelming bogeyman that it might first appear, and it should be possible to tackle in the years to come.

Reference:
Hirschhorn, J. N., & Daly, M. J. (2005). Genome-wide association studies for common diseases and complex traits. Nature Reviews Genetics, 6, 95-108.

(Republished from GNXP.com by permission of author or representative)
 
• Category: Science • Tags: Genetics 
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While reading through a Nature Genetics Review article, I came cross a link to this catalog of published genome-wide association studies. Pretty cool stuff.

(Republished from GNXP.com by permission of author or representative)
 
• Category: Science • Tags: Genetics 
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Andrew Sullivan points to a post by DJ Drummond which makes the claim that the polls are significantly biased towards the Democrats. This is a perfect example of partisanship taking precedence over facts, and it thus deserves a thorough fisking. Drummond begins:

it needs noting that all of the major polling organizations are based in locations where liberals are strongest and conservatives weakest, where ‘democrat’ and ‘republican’ take on meanings wildly different from the rest of the country. The people making the executive decisions at these polls, most likely including the wording and order of polling questions, whether to focus on urban or suburban areas, the weighting of political affiliation, and the definition of ‘likely voter’, are most likely in regular contact and association with the most liberal factions of politics. It does not mean that they have deliberately skewed their decisions to support Obama, but it is obvious that there is an apparent conflict of interest in their process modality.

To begin with, most major *conservative* media outlets (e.g Fox News, the National Review) are located in these regions. Drummond suggests that through some kind of opinion osmosis, pollsters in urban areas tilt their polls towards liberals. The evidence suggests this contention is wrong:

  1. Fox News and Rasmussen (both Republican-owned) are going in the same direction as the average of all the other polls (including those funded by liberal/democrat organizations). The latest Fox Poll shows Obama leading by 9. Contrast this with the current pollster average difference of 8.
  2. Pollsters polled the Bush-Kerry election correctly, accurately predicting a close victory by Bush. Also, they under-polled Gore by 3 points.
  3. John McCain is campaigning most heavily in the swing states identified by the supposedly liberal-biased polls. His campaign, like all presidential campaigns, has its own internal polling. Apparently it matches up with Gallup et. al to a great degree.

Drummond goes on to make some specific arguments for his point of view:

most people do not have the interest to stop and take an 8-to-10 minute interview, especially from someone they do not know calling them up when they are likely to be busy doing something else. It’s been established as well, that democrats in recent years are more willing to take part in polls than republicans, possibly due to perceived bias on the part of the media. But it is quite important to know if the pollsters were getting one person in ten to take the poll, or only one person in fifty, because the people not interviewed matter just as much as those who do participate. Yet I have never yet seen a poll this year that publishes response rates.

Although this has nothing to do with the claimed liberal bias of polling organizations, it is a generic methodological issue worth discussing. Response rates are typically in the 10 to 25% range (PDF link). In general, the candidate who excites their base more (regardless of party) will have a higher response rate from telephone polls. The argument is that this inflates estimates of their support. However, the evidence suggests the opposite; the candidate with more enthusiasm behind him/her inspires people not only to pickup the phone but also go to the voting booth.

It’s also worth noting that Drummond ignores any methodological biases which would inflate McCain’s estimated share of the vote. For example, people who either have no home phone or use cell phones are typically not being sampled. These people are disproportionately young and/or poor (both demographics favor Obama).

This is a big one that a lot of folks miss. I have noticed in the details, that all of the polls are asking about the public’s opinion of the economy, and of their opinion of President Bush, even though he is not running this time.

These questions have been asked for decades, under both Republican and Democratic presidents. That Drummond is unaware of this shows that he doesn’t know enough about polling to criticize it.

many polls ask a question about John McCain just after asking about the voter’s opinion of President Bush, subtly linking the two men.

Polls that ask about the election first match the current polling trend. See, for example, that recent Fox News Poll where Obama leads by 9 (PDF link). This poll is in following with the majority of them in asking about Bush *after* they ask about the election.

no questions have been asked about approval of the specific performance of either Majority Leader Reid or Speaker Pelosi, and no other politician is linked to Barack Obama in the same way that polls link President Bush to John McCain.

First off, it’s a rarity to poll about the performance of the Speaker or Majority Leader, regardless of whether they’re Republican or Democrat. Second, it’s not true that there haven’t been polls dealing with Obama’s connections. There have been several polls asking about voters’ opinions on Obama’s connections to Ayers and Wright.

Polls taken since Labor day have not mentioned foreign policy at all. There are no questions regarding Russia’s invasion of Georgia, nor of Iran’s nuclear weapons programs, nor about China’s intentions viz a viz Taiwan, even though these are current events which have great significance in a presidential race, yet all of the polls are ignoring them. Again, the economy-only focus betrays a bias which violates the principles of the NCPP.

There have been polls on foreign policy since labor day, and it takes only a simple Google search to know this. See for example this one by the New York Times. The focus on the economy (both by the polls and by the candidates themselves) has not come about because of liberal bias, but because voters indicate that this is what matters to them.

The thing most folks forget about polls which get published in the media, is that the polls’ first need is not to accurately reflect the election progress and report on actual support levels; it’s about business.

This is a false dichotomy. These needs overlap to a great deal. SurveyUSA went from a no-name to the most respected pollster among bloggers (and, eventually the press) during the dem primaries simply because it more accurately predicted outcomes in the Democratic primary than anyone else. (They were frequently the outlier from the pack, by the way, and we’ll get to that in a second). As a result they got more web traffic and citations. So there’s definitely an economic and social incentive to give accurate polls. For a “conservative”, this guy sure has a great disrespect for market efficiency.

you really think republicans or independents got more excited about Obama because of his convention, or that democrats and independents were more likely to vote for McCain because of the GOP convention? When you think about it, it should be obvious that these bumps are artificial u
nless there is a clear cause to show a change in support.

A simpler hypothesis is that the polling companies are accurately registering a slight increase in support for a given candidate in response to their increased positive media attention.

There has been unprecedented manipulation of demographics, corrupting even the raw data to the point where effective resolution of public opinion is doubtful. This might be described as an honest mistake, if one is willing to accept greed as an honest motive. Gallup, for example, who has more experience than any other polling group and who therefore should have known better more than anyone else to fiddle with the weights.

Where is the data? Where is the evidence that Gallup is not weighting demographics accurately? Drummond says he has written on it previously, but a search of his site for “gallup census” shows no posts which actually show the gallup weighting to be at odds with the US census. Demographics weighting varies as a function of the pollster. It’s worth noting that despite their different weightings, the major pollsters agree that Obama is leading by at least 5 points right now.

So OK, Gallup is having a bad year, but what about the rest? Well, there the phrase to consider is follow the leader.

I’ve been following the polls since the primaries, and I can safely say: that hasn’t been very true for this election or the dem primaries. There have been spreads as great as 15 points (see for example New Hampshire in the Democratic Primary) between various pollsters at several points in this year and last. The models, and occasionally the outcomes, have been significantly different from one pollster to the next. This guy needs to compare SurveyUSA to Gallup to Public Policy Polling before he writes another post accusing them of following one another.

So, could I be wrong? I have to be honest and admit that I could.

That’s good to hear, because he actually is wrong. Here’s why:

That McCain is more experienced with the key issues than Obama was ignored, that the historical significance of the debates shows that the effects appear several weeks later was also ignored. That the economy could be as reasonably blamed on the democrat-controlled Congress as on the republican President was never considered. That character would be a salient factor in the decisions of voters was rejected out of hand.

Wishful partisan thinking. Drummond wishes that people supported his president and candidate and issues, but because they don’t he criticizes the data which proves otherwise.

(Republished from GNXP.com by permission of author or representative)
 
• Category: Science • Tags: Politics 
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In Obama’s unexciting review of the Bell Curve, he remarked:

no one disputes that children whose mothers smoke crack when they’re pregnant are going to have developmental problems.

The relevant studies reveal a more complex picture, though. The effects of prenatal cocaine exposure on IQ remain heavily contested to this day. However, recent evidence from Bennett et al points to a 3 to 5 IQ point drop, on average. This is the most recent study on this subject that I’m aware of.

Interestingly, in following with a few previous studies, it was found that boys suffer a greater cognitive loss from prenatal cocaine exposure than girls. Also, the study found that 9 year olds had equally fewer IQ points as their 4 year old counterparts, countering to a certain extent the idea that the IQ loss goes away as development progresses.

If Bennett’s numbers are correct, they have small– but significant– implications for the Black-White IQ gap. Unlike tobacco and alcohol, which are used by pregnant white and black women at about equal rates and intensities on average*[1], black women are much more[2] likely than white women to use cocaine or crack while pregnant. This is relevant to behavioral genetic studies– both past and present– which have aimed to understand the relative contributions of genetics and environment to the IQ gaps. There is no way, as far as I know, to extract prenatal factors like cocaine use from measures of heritability without explicitly measuring such inputs. As far as adoption studies in particular, it stands to reason that women who place their babies up for adoption exceed the rest of the US population in pregnant cocaine use. An interesting thing about the Scarr adoption study is that all of the mothers of the half-black kids were white.

[1] Today, that is. 1989 was the earliest year I could find data for, and in that year the pattern is starkly different from today– the black-white ratio in fetal alcohol syndrom for this year has way more alcohol use by pregnant black women than pregnant white women, and also much higher rates of fetal alcohol syndrome among black babies. I’m not sure if the rates were comparable in say the 70′s, when the Scarr adoption study was performed. That would be interesting data if anyone happens to have it.

[2]~12 times more in the second link, from 1994

*Source for the alcohol/tobacco/fetal alcohol syndrome rates is the CDC.

(Republished from GNXP.com by permission of author or representative)
 
• Category: Science • Tags: IQ 
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The evidence is clear — but often ignored
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