Thursday, 8 December 2016

Der tag


Daily total 5018

Thank you to the 5018 readers who looked in on “Psychological Comments” yesterday.


Not complaining, just curious.

For the previous highest daily total see:

Wednesday, 7 December 2016

Faking good on PISA


Faking good on PISA


One of the delights of being a member of a community of researchers in the modern age is the speed with which colleagues can come together to answer a question and scope out a solution to a problem.

Steve Sailer has looked at the most recent PISA results, which he has been discussing generically for many years.

He pointed out that in some countries a large proportion of eligible children don’t show up in the statistics. Could it possibly be the case that they are discretely told to stay at home, because national pride is at stake? Perish the thought! He pointed out that Argentina had apparently made stellar gains, but a commentator on his blog pointed out later that there was so much cheating in the Argentine provinces that the results had to be discarded, and the declared results are for Buenos Aires only, so probably higher than the national figures, or so the porteños would have you believe. Incidentally, it is only recently that Argentina has had economic data, such as for inflation, that could be vaguely trusted, so they are only just in the Truth Recovery phase.

Cheating is the easiest way to boost results. Teachers can look at the questions some days before the test, and do a crash course in “revision” for the class. This makes teachers, children, parents and governments happy. PISA says it has methods to ensure security and detect cheating, but Heiner Rindermann also has his own ability to look carefully at PISA’s published results, and rejects some of them on the grounds of improbability.

Anatoly Karlin also had a look at the dataset and discussed the disappointing performance of China and other eastern countries, with Russia doing better. Get his full account here:

I wondered how big the effect of such selective non-attendance on the examinations might be. There is also the confounder that age at ending secondary education varies between one country and another, so that must be factored into the equation.

Emil Kirkegaard suggested an approach, and after discussions with me and Gerhard Meisenberg, sorted it out quickly. Have a look at the full process here:

Emil had also asked Heiner Rindermann to comment, and he came in a few minutes later, with a detailed publication (not yet published, so I cannot show it to you) and a rule of thumb adjustment you can apply to all the countries.

Heiner says:

School attendance rate of 15 year old youth (usually, but not always,  given in PISA reports, usually somewhere at the end).
Do not confuse with participation rate in PISA study.

Per each percent point not attending school subtract 1.5 SASQ points (equivalent 0.225 IQ points). That is a rule of thumb.

I have made a smaller correction for countries at low ability levels - in such countries pupils in school do not learn much.

Not bad for a few hours of internet time.

A few hours later, Steve Sailer had further and better particulars on the results:

So, where does this leave us with the PISA results? First, it gives me a chance to quote myself, one of the consolations of a lonely blogger: “Nobody gets round sampling theory, not even the Spanish Inquisition.” 

Second, and arising from the quote, the consequence is that the PISA results are only generalizable if the sample is a fair selection of the relevant group. In my view, to understand the abilities of a nation, the relevant group should be the entire age cohort. If many 15 year olds have already left school then a school sample will always be a partial indicator of a nation, and will very probably flatter it. This is because weaker students find school frustrating and leave, whereas the brighter ones enjoy studying, understand its long term benefits, and stay in education as long as they can. Further, if teachers ensure that even among those still staying at school the weaker students fall discretely ill on the day of testing, then the results can be massaged upwards. Spotting weaker students is easy for teachers: they can quickly determine it from student questions, and more accurately determine it by marking their class test papers.

Third, I do not want to reject PISA results, because local examination results share many of the same problems. In any nation where some teenagers leave school early the local examination results will be better than the actual national average. Equally, if within a school cohort not everyone takes the same national examination, the same flattering distortion takes place.

Fourth and finally, I think it best to study PISA results once they have been corrected to account for incomplete age cohorts in the Rindermann fashion, or in some elaboration and refinement of that technique.  Absent that, they have a large error term and present too rosy a picture of national scholastic attainments.

Thursday, 1 December 2016

Does Age make us sage or sag?


If you are of sensitive disposition, and certainly if you are over 60 years of age, look away now. Age is not good news for the thinking person. The results can be summarised in one word: decline. If you protest that I have been too brief, I can triple the word count: decline and fall.

Can we find more appealing results by taking another large sample, and applying more extensive measures of mental ability?

Elise Whitley, Ian J. Deary, Stuart J.Ritchie, G. David Batty, Meena Kumari, Michaela Benzeval. Variations in cognitive abilities across the life course: Cross-sectional evidence from Understanding Society: The UK Household Longitudinal

Background: Populations worldwide are aging. Cognitive decline is an important precursor of dementia, illness and death and, even within the normal range, is associated with poorer performance on everyday tasks. However, the impact of age on cognitive function does not always receive the attention it deserves.


We have explored cross-sectional associations of age with five cognitive tests (word recall, verbal fluency, subtraction, number sequence, and numerical problem solving) in a large representative sample of over 40,000 men and women aged 16 to 100 living in the UK.


Women performed better on word recall tests and men had higher scores for subtraction, number sequence and numerical problem solving. However, age-cognition associations were generally similar in both genders. Mean word recall and number sequence scores decreased from early adulthood with steeper declines from the mid-60s onwards Verbal fluency, subtraction and numerical problem solving scores remained stable or increased from early to mid-adulthood, followed by approximately linear declines from around age 60. Performance on all tests was progressively lower in respondents with increasingly worse self-rated health and memory. Age-related declines in word recall, verbal fluency and number sequence started earlier in those with the worst self-rated health. There was no compelling evidence for age dedifferentiation (that the general factor of cognitive ability changes in strength with age).


We have confirmed previously observed patterns of cognitive aging

Age and ability


Sharp declines for word recall, verbal fluency and number sequences; declines after 60 years of age for numerical problem solving, and even some gradual decline on subtraction. Ironic, is it not, that after the subtraction of all our skills, subtraction itself should be spared?

Somewhat chastened by these findings, I turned to another paper in the hope it would cheer me up. Written by the same incredible Edinburgh gang, who have cornered the market in ageing research, they try to find what makes people age well from a cognitive point of view. Surely with a few mental exercises and a good helping of fresh vegetables all will be well with me?

Stuart J. Ritchie,, Elliot M. Tucker-Drob, Simon R. Cox, Janie Corley, Dominika Dykiert, Paul Redmond, Alison Pattie, Adele M. Taylor, RuthSibbett, John M. Starr, Ian J. Deary

Predictors of ageing-related decline across multiple cognitive functions.


Ageing hedgehog plots

I call these “the hedgehogs”. They show that if you give every ageing person the same starting point then they age at different speeds. This gives us all hope. It may be delusional hope, but it is hope nonetheless. What makes some of us age gracefully?

It is critical to discover why some people's cognitive abilities age better than others'. We applied multivariate growth curve models to data from a narrow-age cohort measured on a multi-domain IQ measure at age 11 years and a comprehensive battery of thirteen measures of visuospatial, memory, crystallized, and processing speed abilities at ages 70, 73, and 76 years (n= 1091 at age 70). We found that 48% of the variance in change in performance on the thirteen cognitive measures was shared across all measures, an additional 26% was specific to the four ability domains, and 26% was test-specific. We tested the association of a wide variety ofsociodemographic, fitness, health, and genetic variables with each of these cognitive change factors. Models that simultaneously included all covariates accounted for appreciable proportions of variance in the cognitive change factors(e.g. approximately one third of the variance in general cognitive change). However,beyond physical fitness and possession of the APOEe4 allele, very few predictors were incrementally associated with cognitive change at statistically significant levels. The results highlight a small number of factors that predict differences in cognitive ageing, and underscore that correlates of cognitive level are not necessarily predictors of decline. Even larger samples will likely be required to identify additional variables with more modest associations with normal range heterogeneity in aging related cognitive declines.

The study has three waves of testing over six years (70 to 76 years of age), and a broad range of cognitive measures. It is also informed by the original measure of intelligence at age 11, so far better grounded than most research.

Here are the key findings:

Ageing and digit symbol

If you want a really good test of decrement of ability for the over 70s, use Digit Symbol substitution. Better than a brain scan any day.

About half of the drop in function across the 13 cognitive measures is shared. “It all goes together when it goes” is at least half true.

Brighter children become brighter, healthier, and fitter older adults. This ‘preserved differentiation’ appeared to last into the eighth decade of life.

The most robust and consistent predictor of cognitive change within old age, even after control for all the other variables, was the presence of the APOEe4 allele. APOEe4 carriers showed over half a standard deviation more general cognitive decline compared to non-carriers, with particularly pronounced decline in their Speed and numerically smaller, but still significant, declines in their verbal memory.

Women had significantly less general cognitive decline than men, mainly centered on Crystallized ability.

No evidence for a relation between education (or social class) and the slope of any of the cognitive factors.

The three fitness indicators weren’t much related to the rate of cognitive decline, but taken together there was a higher correlation, but nothing in this study to test the idea that improving physical functioning would have had a cognitive sparing effect.

If you don’t like the general drift of these results you may wish to say that age is a social construct, that the definition of old age is arbitrary, that countries differ considerably in their classifications of the elderly, that there is no precise point at which a person becomes old and that the whole concept is meaningless, or indeed totally meaningless. You could also argue that people have many abilities which have not been measured by the particular tests used in these studies, and that those untested abilities probably show no decrements. For example, tuneless whistling, stirring coffee while meditating, the recollection of things past, and smiling faintly at the last but one joke in a conversation. Each person shows their genius in their own way.

Back to the results. Perhaps a younger reader would be willing to take a quick look at all of them to make sure that I have understood them properly.

On reflection, I would ask the young reader that if this complex task takes you only a moment, please delay for a while before responding to me, so as not to make the contrast in our processing speeds too evident.

Friday, 25 November 2016

Intelligence, emotions and personality


In my day, intelligence and personality required completely different lectures. Indeed, the subject areas did not overlap at all and each had a very different tone: intelligence involved intelligence tests, in which it was possible to do badly, which was certainly a disappointment to many in the class, and a source of much anti-IQ resentment.

Personality, on the other hand, was a bit less daunting, in that there were said to be no wrong answers. That wasn’t entirely true, but there were crumbs of comfort for almost everybody. It was implied that all personality types had their uses, “it takes all types to make a world” and that they would form a happy team if selected and organised properly.

Then some new ideas came up. The first and highly popular notion was that in addition to boring old analytic intelligence some people had an ability which really mattered: emotional intelligence. The term quickly became synonymous with a sensitive, perceptive, positive person, able to succeed in real life in ways that a sharper, colder, analytic mind would find difficult, if not impossible. The emotionally intelligent were intelligent about emotions: they could spot them and manage them, secret agents of the unconscious. The corporate world embraced the notion of EQ,  the Emotional Quotient they sought in their employees.

It took some time for those who had been actually researching the area to make the public understand that the popular term conflated two apparently different things: aspects of personality associated with success in life, and the ability to understand other people’s emotions. The first half was just plain old Personality. The second half was what the researchers were interested in: whether some people had a specific skill in understanding other people’s emotional states.

So, leaving aside personality, and looking only at the putative new emotional-state-understanding-skill,  they designed tests of emotional intelligence. This proved to be quite difficult. After a decade of work they found that there was some evidence for this skill, but to my reading no more outstanding than a minor subtest in a general intelligence test. Working out the emotions of others is related to general intelligence.

Meanwhile, over in the personality camp, not only had the field agreed that 5 main factors were a good resolution of the observed findings on the many proposed dimensions of personality, but some went further, and said that those five factors could be resolved into one general factor of personality. I like this idea, if only because I noted how much workplace gossip centred round complaining about uncooperative people, and the cooperative/uncooperative axis is an important aspect of the general factor of personality.

Now van der Linden et al. come along with a meta-analysis which seems to resolve the matter very neatly. They argue that the general factor of personality and emotional intelligence are one and the same thing.

van der Linden, D., Pekaar, K. A., Bakker, A. B., Schermer, J. A., Vernon, P. A., Dunkel, C. S., & Petrides, K. V. (2016, November 14). Overlap Between the General Factor of Personality and Emotional Intelligence: A Meta-Analysis. Psychological Bulletin. Advance online publication.

We examine the relationship between the general factor of personality (GFP) and emotional intelligence (EI) and specifically test the hypothesis that the GFP is a social effectiveness factor overlapping conceptually with EI. Presented is an extensive meta-analysis in which the associations between the GFP, extracted from the Big Five dimensions, with various EI measures is examined. Based on a total sample of k 142 data sources ( N 36,268) the 2 major findings from the meta-analysis were (a) a large overlap between the GFP and trait EI (r .85); and (b) a positive, but more moderate, correlation with ability EI (r .28). These findings show that high-GFP individuals score higher on trait and ability EI, supporting the notion that the GFP is a social effectiveness factor. The findings also suggest that the GFP is very similar, perhaps even synonymous, to trait EI.

general factor personality and emotional intelligence


Scoring high or low on the GFP would not necessarily indicate a good versus bad personality (Rushton & Irwing, 2011). Instead, it would mainly reflect the extent to which one uses emotional knowledge and skills in order to cooperate with others and obtain personal goals. Note that such knowledge and skills can, in principle, be used for ethical (e.g., maintaining friendships and working in teams) or unethical (e.g., deceiving and corrupting others) causes. Thus, similar to EI, the GFP can have a “bright” as well as a “dark” side.

In the fullness of time, instead of having to rely on theoretically fuzzy linear combinations of the Big Five factors, we will be able to utilize coherent constructs that have been specifically aligned to the core psychological processes underlying the emotional and social aspects of human behaviour.


This is interesting work, but there are some cautionary notes. No intelligence tests were given, so we cannot really say how much these personality aspects relate to real ability. Nor did they include measures of social desirability, also known as lying. Odd as it may seem, some respondents do not admit to having lousy personalities and appalling habits. In my view personality is best measured by observed behaviour, not questionnaire responses.

All those points apart, (which the authors put forward as limitations), they do not hide the fact that this is an elegant simplification of  some complicated constructs, and may indeed lead us to a more coherent understanding of emotional and social behaviour.

Wednesday, 23 November 2016

Fourth Blog Birthday


Birthday candle


A blogger is a harmless drudge, a filter paper between a sack of coffee beans and a small expresso.

On the positive side, there is a sack of information to be read in the torrent of publications on intelligence. On the negative side, there is an even greater Sargasso Sea of mangled misunderstanding about human ability.

The torrent of publications would be unmanageable were it not for trusted researchers, many first met at ISIR conferences, who guide me to what they think of value, and at my request send me their own papers when they think they would suit the interests of Psychological Comments: interesting, new, and going faithfully in the direction of the evidence, not the preferred argument. I cannot always comment in detail on all of them, and in future I will try to at least mention those I have read even if I have not commented on them.

The Sargasso Sea of mangled misunderstanding I come across in newspapers and broadcast media never fails to irritate me. At times I feel I patrol the news, or at least that part of it which relates to human ability and life outcomes, on the lookout for egregious errors. The themes are repetitive: IQ does not exist; or cannot be measured; or can be measured much better by multiple intelligence, personal intelligence, emotional intelligence, rationality or motivation; can be boosted by a myriad of techniques including heroic training routines, more sleep and lunchtime naps, alertness drugs, and cunning new methods of instruction; and intelligence isn’t much use anyway, because achievement depends on motivation, luck, class, money, privilege; and finally, too much intelligence drives people nuts.

After all that provocation, it is with some surprise that I find myself still here, writing for those who bother to read essays, and who are interested to note how so many claims about intelligence fall apart if you bother the plod through the whole paper, and the appendixes. Thanks for being loyal readers.

To those who come across the blog, and then leave promptly in dismay at the Tables, Figures, Supplementary Appendixes and statistics: I am sorry your stay was so brief, but I do not blame you. Reading this blog will not boost your IQ nor the dimensions or performance of your private parts. It may, however, enlarge your understanding of intelligence research.

As per tradition, the blog birthday picture always shows one candle, so that we can acknowledge the triumph of survival undimmed by the metronome of mortality.

Here are are the top ten all time posts:

4th blog post totals

Most of these are old favourites which have first mover advantage. Good to see Digit Span rising so well.

Top ten referring sites

4th blog referring sites

Twitter is the big leader, Google almost equal in size, but a respectable number of readers come straight to the blog. Thanks to Steve Sailer and others at and HBDchick and others elsewhere for their support.

Top ten reader nations

4th blog countries

The US leads the way, 5 times more numerous than the UK in second place. Russia surprises me (Anatoly Karlin may have the explanation), also Ukraine.

Pageviews totals for 4th Blog Birthday


4th blog total pageviews


Last four years of total page views

               Pageviews     Twitter followers

Year 1           71,701              199

Year 2        313,753              597

Year 3        657,875              1,457

Year 4      1,o18,236          2,383


According to Klear, my tweets are seen by a “true reach”  average of 516 users (though individual “impressions” can be as high as 10,000). My followers are 30 years of age on average, 74% men, and 30% overall are considered influential.


I have written 755 posts over these 4 years. I have achieved more readers than I imagined possible. Getting over a million page views is a big deal for me. I am sure that my blog has been read more in 4 years than my publications in 48 years. Indeed, because I published relatively little, I can be sure about it. If only blogging had been an option when I started out on my career, such as it was. However, lest I seem to be sneering at the Past, the  5 or 6 television programs I presented (usually 45 minutes long) were watched by one or two million viewers; the news interviews (usually 2 minutes long) could get audiences of five million, and the Chilean miners coming out one by one from their collapsed mine (one whole day in the BBC studio) got a good chunk of the reported one billion global audience. Old fashioned media are good at covering big events.

I digress. Back to blogging. I can still remember wondering if anyone would read my comments, and whether it was worth continuing. Even after a million page views it still feels as if I am whispering against a barrage of loudhailers.

Now over to you. Bring at least one person to read the blog, preferably a researcher, lecturer, teacher or student. Just one.

Thanks for reading.

Thursday, 17 November 2016

Stereotypes about immigrant criminality


Writing a blog can be fun. Post something up one day, get someone writing in with a good tip about another subject for the next day.

The notion that immigrants are criminal has been described as a stereotype. As you know, a stereotype is a preliminary insight, the first step in noticing differences and encapsulating them into an association. Holding a stereotype about immigrants being criminals could be wrong and unfair. It could also be accurate and prudent.

How accurate are stereotypes about immigrants and crime? Here is a relevant paper from the United Kingdom.


The author says: Public beliefs about immigrants and immigration are widely regarded as erroneous. For example, members of the public typically overestimate the immigrant fraction of the population by ~10–15 percentage points. On the other hand, popular stereotypes about the respective characteristics of different groups (e.g., sexes, races, nationalities) are generally found to be quite accurate.

The present study shows that, in the UK, net opposition to immigrants of different nationalities correlates strongly with the log of immigrant arrests rates (r= .77; p= 0.00002; 95% CI = [.52, .90]) and with the log of their arrest rates for violent crime (r= .77; p= 0.00001; 95% CI = [.52, .90]).

This is particularly noteworthy given that Britons reportedly think that an immigrant’s criminal history should be one of the most important characteristics when considering whether he or she should be allowed in to the country. Moreover, the associations are not accounted for by a general opposition to non-Whites, non-Westerners, foreigners who do not speak English, Muslims, or those from countries with low average IQ. While circumstantial in nature, the study’s findings suggest that public beliefs about immigrants are more accurate than is often assumed.

He adds: In Europe, immigrants from the West and East Asia tend to have lower crime rates, while those from the Middle East, Africa and South Asia tend to have higher crime rates (Kirkegaard, 2014; Kirkegaard, 2015). Note that this disparity is probably due to a combination of factors: relatively stable country-of-origin characteristics, the selectivity of immigrants with respect to their countries-of-origin, and perhaps differences in the treatment of immigrant groups upon arrival.

Crime figures from the Metropolitan Police for arrests 2008-2012 were used as the comparison.

Immigrant arrest rates London


Public beliefs about immigrants and immigration are widely regarded as erroneous. Yet popular stereotypes about the respective characteristics of different groups are generally found to be quite accurate. The present study has shown that, in the UK, net opposition to immigrants of different nationalities correlates strongly with the log of immigrant arrests rates and the log of their arrest rates for violent crime.

Indeed, they are consistent with a model of immigration preferences in which individuals’ expressed support or opposition to immigrants from different nationalities is informed by rational beliefs about the respective characteristics of those immigrant groups. The main limitation of this study is the lack of data on other characteristics of immigrant groups living in the UK, such as education, income or welfare usage (see Kirkegaard, 2014; Kirkegaard, 2015).

Read the whole paper here:

Wednesday, 16 November 2016

The accuracy of stereotypes


immigrants in Denmark


Are immigrants more likely to claim benefits, or is this a stereotype?

A stereotype is a preliminary insight. A stereotype can be true, the first step in noticing differences. For conceptual economy, stereotypes encapsulate the characteristics most people have noticed. Not all heuristics are false.

Here is a relevant paper from Denmark.

Emil O. W. Kirkegaard and Julius Daugbjerg Bjerrekær. Country of origin and use of social benefits: A large, preregistered study of stereotype accuracy in Denmark. Open Differential Psychology.


This study is interesting, in that it was pre-registered, so its absence would have been noticed.  It compares stereotypes against actual data to get a test of accuracy. I was particularly struck by how the authors studied the answers at each wave of data collection, and tracked down those who gave perplexing answers, then refining their survey questions to reduce misunderstandings.

The paper also points out an unremarked aspect of stereotypes: they may be too weak. Stereotypes have to show a correlation with the facts, and be good predictors. You have to get the slope right, and also the intercept. It is not enough to have a vague notion that immigrants are on benefits, you ought to be able to estimate how many are on benefits.  A stronger stereotype would be a more accurate perception of reality.

A nationally representative Danish sample was asked to estimate the percentage of persons aged 30-39 living in Denmark receiving social benefits for 70 countries of origin (N = 766). After extensive quality control procedures, a sample of 484 persons were available for analysis. Stereotypes were scored by accuracy by comparing the estimates values to values obtained from an official source. Individual stereotypes were found to be fairly accurate (median/mean correlation with criterion values = .48/.43), while the aggregate stereotype was found to be very accurate (r = .70). Both individual and aggregate-level stereotypes tended to underestimate the percentages of persons receiving social benefits and underestimate real group differences.
In bivariate analysis, stereotype correlational accuracy was found to be predicted by a variety of predictors at above chance levels, including conservatism (r = .13), nationalism (r = .11), some immigration critical beliefs/preferences, agreement with a few political parties, educational attainment (r = .20), being male (d = .19) and cognitive ability (r = .22). Agreement with most political parties, experience with ghettos, age, and policy positions on immigrant questions had little or no predictive validity.
In multivariate predictive analysis using LASSO regression, correlational accuracy was found to be predicted only by cognitive ability and educational attainment with even moderate level of reliability. In general, stereotype accuracy was not easy to predict, even using 24 predictors (k-fold cross-validated R2 = 4%).
We examined whether stereotype accuracy was related to the proportion of Muslims in the groups. Stereotypes were found to be less accurate for the groups with higher proportions of Muslims in that participants underestimated the percentages of persons receiving social benefits (mean estimation error for Muslim groups relative to overall elevation error = -8.09 %points).
The study was preregistered with most analyses being specified before data collection began



The observed correlation of .7 is big, and useful. A majority of immigrants from Syria, Somalia and Kuwait are on benefits, as are those from Iraq and Lebanon. Even more to the point, if the benchmark is 25% for Danish citizens, then there are 19 countries with higher benefit rates. More positively, there are countries with lower rates, presumably because they are younger and employed. The data plot does not give us any guide to numbers from each country. However, later in the paper it is shown that immigrant population size is not relevant in judging benefit rates accurately.

The best predictor of having accurate stereotypes was cognitive ability (81% of simulations), followed by educational attainment (74% of simulations). Respondents underestimate the number of Muslims on benefits.

This is a very good paper. Data handling is exceptional, and well explained. There are lots of Figures and Tables. The sample is large and representative. The results have been looked at carefully, to identify those who participated without paying much attention to the questions. The data are available for re-analysis.

The high accuracy of aggregate stereotypes is confirmed. If anything, the stereotypes held by Danish people about immigrants underestimates those immigrants’ reliance on Danish benefits.

Saturday, 12 November 2016

Losing vector directions


A few hours ago I posted up a commentary on a paper:

Brad Verhulst, Lindon J. Eaves, Peter K. Hatemi.  Correlation not Causation: The Relationship between Personality Traits and Political Ideologies. Am J Pol Sci. 2012; 56(1): 34–51.

Somewhat warily I added: I have scrabbled around for some guidance on this (personality and political attitudes) and came across a single paper to start the ball rolling. You find the meta-analysis on political attitudes and we are well on our way.

Sure enough, a single paper is an insufficient basis for a comment, particularly when the authors in an Erratum later admit that:

The interpretation of the coding of the political attitude items in the descriptive and preliminary analyses portion of the manuscript was exactly reversed. Thus, where we indicated that higher scores in Table 1 (page 40) reflect a more conservative response, they actually reflect a more liberal response.

My thanks to reader LemmusLemmus.

I have written to the author of the Erratum to ask if the original miscoding was intended as a projective test for readers. I will await the response, but the paper, in that polite phrase, is “not suitable for hypothesis testing”, and in my view should be set aside.

A.E. Maxwell would have said “get to know your data before worrying about statistical tests”.



Losing an election


Losing an election is no fun. Hopes are dashed, and at least 4 years must pass (5 in the UK) before electors get a chance to vote the other lot out. Deferred gratification is a test of character.

It is natural for the losing side to feel incredulous when their side is defeated, particularly if opinion polls had given them false hope of victory. Since most people consort with like minded friends, they find that most of their social network  have the same political opinions. This makes the loss incredible, because their personal experience validates a firmly held view, and they are unaware that it is based on a very restricted sampling of opinion. A certain egocentric perspective is required to blot out the full range of human opinion so effectively. To resurrect a battered word, diversity of opinion is part of life, and the losing side must always recognize that.

Ever curious, I wonder if the Left are poorer losers than the Right. The null hypothesis, of course, is that a political loss hits both sides equally, and each lose equally badly, whatever their politics.

Is this true?

I have scrabbled around for some guidance on this, and came across a single paper to start the ball rolling. You find the meta-analysis on political attitudes and we are well on our way.

Brad Verhulst, Lindon J. Eaves, Peter K. HatemiCorrelation not Causation: The Relationship between Personality Traits and Political Ideologies. Am J Pol Sci. 2012; 56(1): 34–51.

The authors say:

The assumption in the personality and politics literature is that a person's personality motivates them to develop certain political attitudes later in life. This assumption is founded on the simple correlation between the two constructs and the observation that personality traits are genetically influenced and develop in infancy, whereas political preferences develop later in life. Work in psychology, behavioral genetics, and recently political science, however, has demonstrated that political preferences also develop in childhood and are equally influenced by genetic factors. These findings cast doubt on the assumed causal relationship between personality and politics. Here we test the causal relationship between personality traits and political attitudes using a direction of causation structural model on a genetically informative sample. The results suggest that personality traits do not cause people to develop political attitudes; rather, the correlation between the two is a function of an innate common underlying genetic factor.


Personality and political views

There are correlations between tough-mindedness (Psychoticism on the Eysenck personality inventory), social desirability (the Lie scale) and Neuroticism and political opinions on military, social and economic attitudes.

The authors say:

Higher P scores correlate with more conservative military attitudes and more socially conservative beliefs for both females and males. For males, the relationship between P and military attitudes (r = 0.388) is larger than the relationship between P and social attitudes (r = 0.292). Alternatively, for females, social attitudes correlate more highly with P (r = 0.383) than military attitudes (r = 0.302).

People higher in Neuroticism tend to be more economically liberal. That is, neurotic people are more likely to support public policies that provide aid to the economically disadvantaged (public housing, foreign aid, immigration, etc). Moreover, Neuroticism is unrelated to social ideology (rfemale = −0.016, rmale = −0.050). This finding suggests that neurotic individuals cope with their anxiety by supporting a “social safety net” or more “liberal” economic policies rather than “liberal” social policies.

They continue: There is also a substantively interesting relationship between Social Desirability and social ideology, which is larger for females (r females = −0.335; r males = −0.255). This facet of personality is highly context dependent, and therefore we can only speculate on this relationship, though our results are consistent with other conceptually similar findings. During the same time period in nationally representative samples, in several other attitude domains, liberal responses were also seen as more socially desirable (Kinder and Sears 1981). Thus, it appears that people who are motivated to present themselves in a socially desirable light also present themselves as socially liberal. This is only the second study we are aware of to explore the relationship between any ideological dimension and social desirability, yet the findings replicate the Verhulst, Hatemi, and Martin (2010) study on an Australian population.

So, the conventional explanation is that we have a personality difference which accounts for a political and behavioural difference. Tough-minded people are conservative in military and social matters, and would be expected to give less of a damn about ruffled feelings. Neurotic worriers want governments to help the disadvantaged, favour foreign aid, public housing and immigration. A proneness to worry may conceivably drive them to feel the pain of others, and to imagine they might one day be in need of such support themselves, so it may not all be altruistic.

Finally, those prone to Social Desirability effects (also known as the Lie Scale, a measure of “faking good”, or being incredibly naïve) are socially liberal.

On the basis of this finding, the loss of an election will be felt more strongly by the Left, mostly because they are tender minded, but also because they are worriers who feel that the poor of the world need help which will now be denied them, and that all of society should desire to be like them in their liberal attitudes (or their desire to be seen as liberal and generous).

From a tough-minded, emotionally stable perspective,  the great Democrat sadness, emotional upset and dismay is just the wailing of the mentally afflicted, wallowing in neurotic catastrophization and self-proclaiming virtue. Republicans see the Democrat response as infantile, the abject collapse of spoilt children who  cannot believe how nasty life has been to them.

From a tender-minded, emotionally sensitive perspective the Republican win is  just an extension of the insensitive, heartless and individualistic lack of concern they habitually show to anyone who gets in their way. Democrats see the Republican joy as demonic parents: violent, fascistic, dangerous; behaviours typical of oppressors who believe that life favours the brutal.

And so endeth the lesson.

However, the authors want more, so they do an ACE analysis, and conclude that a latent common genetic factor drives the development of both personality traits and political attitudes. This gives them their “Correlation not Causation” title, which in fact obscures their argument. They should have titled it “Do Personality Traits and Political Ideologies have a common genetic origin?”

For Extraversion, Neuroticism, and P the common environment is not significant in any of these variables.

The only personality trait that deviates from this trend is Social Desirability, characterized by large genetic and unique environmental variance components; however, there is also a significant, though more subtle, common environmental influence.

For political attitudes, the results are notably different. For the social and economic dimensions, the best-fitting model is the full model of additive genetic, common environmental, and unique environmental influences (ACE). There are sizable additive genetic components and substantial common environmental components to the attitudes, suggesting that individual differences in these attitude constructs are a mixture of genetic, shared, and unique environmental components. In contrast, military attitudes display a pattern of transmission similar to that of personality traits (AE), suggesting that attitudes toward the military are a function of what is learned through unique environmental (nonfamilial) influences and genetic transmission, more so than any common environmental influences.

The results so far suggest that the relationship between personality traits and political attitudes is more likely a function of a common set of genes shared between the personality traits and the political attitudes.

So, as the newspaper headlines would scream: “it’s genetic”. The poor weeping Democrats cannot be blamed for their maudlin display of petulance and tearful threats of exiling themselves to Canada. Nor, indeed, can the rich chortling Republicans be blamed for their heartless offensive comments and their eagerness in sending Mexicans back to their homeland.

Democrats are designed to take offence, Republicans to give it.

Finally, I can join all the other commentators and loftily opine: The Country is Split.

Wednesday, 9 November 2016

Opinion palls


Last night I went to bed expecting a Clinton victory, because although opinion polls can be wrong, the margin of Democrat advantage exceeded the apparent margin of polling error. To further confirm my ineptitude at forecasting, I had also thought Remain would win over Leave in the Brexit referendum, for the same reason.

Today I reflect on some basic psychology, which is that attitudes do not translate directly into actions and, in a further complication, expressed attitudes differ from actual attitudes. This is particularly the case where the attitude is considered socially reprehensible, such as coveting one’s neighbours ox, or wife; being pleased when a rival fails to get a promotion; resenting a newcomer; or disliking someone because a superficial characteristic grates on your nerves.

Of course, I have always known, but often forgotten, that there is a gap between what is thought and said, and a bigger gap between what is said and done.

I also know, but often forget, that public opinion polls habitually use smaller samples than required for proper representativeness,  and that the pollsters then “correct” their raw results using a set of assumptions gained from trying to correct previous errors (turnout rate, for example) whilst also looking over their shoulders at what most other polls are saying, so as to not be the odd one out. Come to think of it, the pollsters’ fascination with finding out what other people are thinking infests the poll companies themselves, and they are guided by what other poll companies are thinking. Polls of polls simply aggregate and confirm the group errors.

Will attention continue to be paid to opinion polls, given their inability to spot what the public really intend to do? The growing awareness that polls are used to influence opinion as much as to measure it has become painfully obvious. They are not trustworthy, and flourish most when people cannot work out their own opinions for themselves. No, I do not want to ban them. I just want to get out of my habit of paying them much attention.

Now, here is a quick check of the predictions I made yesterday against Edison Research exit questionnaires:

Most of all I wonder how years of education, which supposedly indicates an ability to evaluate arguments, will correlate with actual votes, and thereby to test the popular supposition that the better educated voters will shun the Republican candidate. I assume that sex and age will have a minor influence, but the latter might show bigger differences, with older voters more cynical and more likely to vote Republican. Race should not matter at all, because if America is a melting pot then policies not polities should prevail. If races vote en bloc (say more than 65% in one direction) then the woe betide the republic, which will become disunited genetic states.

Years of education



Post-graduates voted Democrat, as expected. However, I did not consider income:


There was some effect of low income boosting Democrat votes, but those with income above $50,000 were not swayed by necessity, and voted according to political preferences. Perhaps the well-educated post graduates took the sorts of degrees which did not boost their income. Psychology, anyone?

Here are the sex differences:


In fact, much bigger than I imagined would be the case.


The age differences were also bigger, though I got it half right, in that older voters were more likely to vote Republican than those younger than 45, and particular than those younger than 30.

As regards race, you will see that I put forward a null hypothesis I did not believe in, but wanted to test. I used to follow the majority in describing the US as a melting pot, but have come to think of it as only a dispersal ground.


Black voters are overwhelmingly Democrat, and can be considered a bloc vote. Hispanic/Latinos and Asian also meet precisely my predicted bench mark of 65% to be considered bloc voters. The “other” voters look as if they have been somewhat considering the actual policies, as do the White voters, but both are not that far off the 65% boundary I plucked out of the air as an indicator of race-based voting. Blacks to an extraordinary degree, and Hispanics and Asians to a large degree jumped left, Whites jumped right.

So, is the summary of this election “it’s race, stupid”? If so, I also predicted a Disunited Genetic States. I doubt it. Governments habitually do less than they promise, and have less influence than they imagine. The great flywheel of habit usually reigns supreme.  Usually.  I will consider this matter further after a good night’s sleep.