[OBG] Sexual selection explains sex and country differences in fluid g
When someone performs multiple regression, especially in case where there is few indep var, I always recommend to test for the presence of interaction (i.e., non linear relationship.

When you try the following :

COMPUTE sex_gdp_interaction=Difference*GDP.
EXECUTE.

REGRESSION
/DESCRIPTIVES MEAN STDDEV CORR SIG N
/MISSING LISTWISE
/STATISTICS COEFF OUTS CI(95) R ANOVA COLLIN TOL CHANGE ZPP
/CRITERIA=PIN(.05) POUT(.10)
/NOORIGIN
/DEPENDENT PISA_Score_Total
/METHOD=ENTER Difference GDP sex_gdp_interaction
/PARTIALPLOT ALL
/SCATTERPLOT=(*ZRESID ,*ZPRED)
/RESIDUALS DURBIN HISTOGRAM(ZRESID) NORMPROB(ZRESID).

The regress coeff for sex, gdp, and interaction are 0.170, 0.426, 0.185. It's clearly different from what you initially have (0.323, and 520). The gender effect has been divided by an half.

When you repeat the same procedure with pisa SD in dependent var., instead of having -0.490 and -0.147 for sex and gdp, you have -0.302, -0.030, -0.226 for sex, gdp, and their interaction, respectively. This means there is virtually no main effect of GDP, and its (direct) effect is only a matter of interaction, (i.e., the effect of GDP, while probably null at low value of sex difference, it increases as the sex difference increases).

Practioners should also and always check for normal distribution of the residuals. Hopefully, they look normal.

MR, in any case, is a sub-optimal way to "control" for covariates (or for what it means). If you need to look at the effect of GDP net of that of gender, you should better use male/female PISA as dependent var, separately, but if that means you have only 1 indep var, MR and bivariate correlation are not distinguishable methods (they produce the same results). For what I have seen, using SD or score for male/female separately makes no difference for the correlation with GDP.
When someone performs multiple regression, especially in case where there is few indep var, I always recommend to test for the presence of interaction (i.e., non linear relationship.

When you try the following :

COMPUTE sex_gdp_interaction=Difference*GDP.
EXECUTE.

REGRESSION
/DESCRIPTIVES MEAN STDDEV CORR SIG N
/MISSING LISTWISE
/STATISTICS COEFF OUTS CI(95) R ANOVA COLLIN TOL CHANGE ZPP
/CRITERIA=PIN(.05) POUT(.10)
/NOORIGIN
/DEPENDENT PISA_Score_Total
/METHOD=ENTER Difference GDP sex_gdp_interaction
/PARTIALPLOT ALL
/SCATTERPLOT=(*ZRESID ,*ZPRED)
/RESIDUALS DURBIN HISTOGRAM(ZRESID) NORMPROB(ZRESID).

The regress coeff for sex, gdp, and interaction are 0.170, 0.426, 0.185. It's clearly different from what you initially have (0.323, and 520). The gender effect has been divided by an half.

When you repeat the same procedure with pisa SD in dependent var., instead of having -0.490 and -0.147 for sex and gdp, you have -0.302, -0.030, -0.226 for sex, gdp, and their interaction, respectively. This means there is virtually no main effect of GDP, and its (direct) effect is only a matter of interaction, (i.e., the effect of GDP, while probably null at low value of sex difference, it increases as the sex difference increases).

Practioners should also and always check for normal distribution of the residuals. Hopefully, they look normal.

MR, in any case, is a sub-optimal way to "control" for covariates (or for what it means). If you need to look at the effect of GDP net of that of gender, you should better use male/female PISA as dependent var, separately, but if that means you have only 1 indep var, MR and bivariate correlation are not distinguishable methods (they produce the same results). For what I have seen, using SD or score for male/female separately makes no difference for the correlation with GDP.

The linear model is the most parsimonious and probably to be preferred. It's likely that any interaction effects are due to statistical flukes.
Also throwing in an interaction effect between sex and gdp seems a bit sketchy, without a theoretical reason for doing so.However, I appreciate your help and am not denying its validity.I just think it's not entirely appropriate for this analysis.
This is an interesting paper which I hope to eventually see published. However, a couple of suggestions. (1) I wonder if height is a good measure to use. These are often self-estimates and are thus not very reliable. As such, it might be better to use a number of different estimates to obviate the unreliability. For example, Lynn did a paper on penis length in different European countries. (2) It strikes me that the paper would be strengthened by using all of the PISA data as there is a high correlation between this and IQ.

The penis data was made up. Lynn apparently found them on the internet and didn't check the source. Philbrick pointed this out to me in an earlier review of a paper I wrote, I think.

That's correct.
The linear model is the most parsimonious and probably to be preferred. It's likely that any interaction effects are due to statistical flukes.
Also throwing in an interaction effect between sex and gdp seems a bit sketchy, without a theoretical reason for doing so.However, I appreciate your help and am not denying its validity.I just think it's not entirely appropriate for this analysis.

In general, the most parsimonious model should be preferred when taking into account model fit. In principle, however, when interaction is present, the model fit must necessarily favor a model with interaction. Theoretically, I still think it's quite interpretable. The results above mean that GDP has no main effect and the strength of its effect depend on the size of the gender difference in PISA. Now the whole thing is to interpret this outcome in light of the theory advanced in your article. I'll try to read the text more carefully and see if I get some ideas.
The linear model is the most parsimonious and probably to be preferred. It's likely that any interaction effects are due to statistical flukes.
Also throwing in an interaction effect between sex and gdp seems a bit sketchy, without a theoretical reason for doing so.However, I appreciate your help and am not denying its validity.I just think it's not entirely appropriate for this analysis.

In general, the most parsimonious model should be preferred when taking into account model fit. In principle, however, when interaction is present, the model fit must necessarily favor a model with interaction. Theoretically, I still think it's quite interpretable. The results above mean that GDP has no main effect and the strength of its effect depend on the size of the gender difference in PISA. Now the whole thing is to interpret this outcome in light of the theory advanced in your article. I'll try to read the text more carefully and see if I get some ideas.

I am afraid you'll have to reread my paper because I've substantially enlarged and updated the introduction with theory, slighly changed discussion and added to methods section. I attach the updated version.
A journalist asked Einstein what he would do if Eddington's observations failed to match his theory. Einstein replied : "I would feel sorry for the God lord. The theory is correct".
Dear Davide Piffer,

Thank you for your submission to Evolutionary Psychology. We have given your submission full attention. However, after consultation with the Editorial board, we have decided that your manuscript is not suitable for publication in Evolutionary Psychology, and thus won't be sent out for in-depth review. I am sorry for being the bearer of what must be negative news. The Editors of Evolutionary Psychology aim to give quick feedback particularly with submissions, which are unlikely to get accepted even after in depth review and/or revision. Alas your submission falls into this category and was therefore rejected at this stage.

Best of luck with your work.

Sincerely,

Bernhard Fink
I've made several changes. It'd be nice if some kind soul could review this paper. https://docs.google.com/document/d/15yXb2_k5pecCRu1VXZGwA37wrOlscfXqDJ2qMXfa19Y/edit?usp=sharing
I'm busy, so I had priorities. I will look at the newest versions. Concerning the message you get from B Fink, it's ridiculous. What is the charge against you ? There is no explanation, no details, I don't know what he is talking about with "Alas your submission falls into this category". Which category ? And i'm sure no one else in the earth would understand what he is saying.
I'm busy, so I had priorities. I will look at the newest versions. Concerning the message you get from B Fink, it's ridiculous. What is the charge against you ? There is no explanation, no details, I don't know what he is talking about with "Alas your submission falls into this category". Which category ? And i'm sure no one else in the earth would understand what he is saying.

Okay, I made a bunch of mostly grammatical corrections <a href="https://drive.google.com/file/d/0B4NGOBcoYImfQ1JlS1VwMGJVNDg/edit">here</a>;. The notes below refer to some of the changes in the file, which are marked.

Regarding sexual dimorphism in IQ, you are basically assuming that genetics is the likely explanation. Of course, IQ is not entirely genetic, and African-American women have had somewhat <a href="http://theunsilencedscience.blogspot.com/2012/04/racial-amplitudes-of-scholastic.html">improving SAT scores</a> relative to African-American men over time. It might be good to mention alternative cultural explanations, like machismo, male-dominance of underground economy pulling men from educational pursuit, family or community breakdown, post-colonial loss of order, differences in economic structure that favor heavy manual labor, etc. You could integrate this with the brain versus brawn dichotomy, but you could emphasize how your predictions based on evolutionary theory fit the data so well.

Don't use sex as an adjective. Use sexual. Maybe "sex differences" and keeping quotations intact are exceptions, but I think consistency should be favored when possible.

Avoid nested parentheses.

Write 0 before decimal points or at least be consistent.

Write out acronyms and name symbols upon first usage, followed by their acronym or symbol in parentheses. (PISA, g)

Line 11 & 257:
I don't think it is clear to say sexual selection increases the phenotype value. I think it is better to say that sexual selection increases the prevalence of a favored phenotype. Only mutation creates novel phenotypes.

Line 18:
"Supporting" would be dangling modifier of "average country male height."

Line 28:
Reserve passive verb tense for avoiding first person.

Line 61:
Check where quotation ends.

Line 68:
Intersexual competition would be boys vs. girls.

Line 71:
It's debatable whether warriors have high status historically, especially in recent history, so say in antiquity.

The following two statements did not have sources:

Line 71:
"Moreover, men in antiquity performed endeavours such as hunting and making war against other tribes or nations, actions which require greater fluid intelligence and strategic planning, and the best warriors and hunters have traditionally enjoyed a dramatic boost in status, which would have translated into better reproductive success."

Line 102:
"Moreover, since sexual selection operates more strongly on males, a greater reduction in variance should be observed in males than in females."

I'm not a psychologist, but I have read that fluid IQ is disputed (Johnson and Bouchard, 2005). I wonder if you should defend the concept briefly or drop the word fluid and just call it intelligence. Even if you accept it, there are problematic aspects to it, such as its higher Flynn effect. Also, there is a perception that women undergo sexual selection to make them less intelligent. I don't know if that's true, but it might be a reason to either add sources or qualify these statements ("might operate more strongly on males").

Line 107:
"Finally, although even natural selection results in lower phenotypic variance for the trait under selection, it does not necessarily predict sexual dimorphism for that trait, which instead fits better with a model that includes sexual selection."

I would completely remove this because I think sexual selection is a subset of natural selection, or perhaps the two are not mutually exclusive.

Line 112 & 290:
Didn't IQ alleles fail to achieve GWAS statistical significance? Avoid "he" when referring to self.

Line 133:
"Assessment assesses" is awkward.

Line 139:
Take out the.

Line 140:
Adding the's makes for consistent use of nouns as labels.

Line 149:
Take out "in."

Line 158:
Wikipedia is not a primary source, and it is always being edited, so readers can't verify your data in the future. I see that the page is a great resource, and each data point comes from a different source, so I don't think it is absolutely necessary to cite each source, but I also would consider it a big improvement, if you did.

Line 178 & 248:
Remove "Confirming expectations." Results section should avoid commentary.

Table 1:
Widen "Difference" to fit one line. Add units where appropriate in headings (GDP). Give description of table after "Table 1." Edit out empty cells. I split the table to do this just for a page break.

Table 2:
Use consistent capitalization with table descriptions. Borders need to be consistent and no empty cells except corner.

Table 3:
I recommend putting notes outside of table.

Line 226:
I recommend describing regression methodology in methods section.

Table 4 & 5:
Remove empty cells.

Line 286:
I think "is" is too definite. I would prefer "seems to be."

Regarding sexual dimorphism in IQ, you are basically assuming that genetics is the likely explanation. Of course, IQ is not entirely genetic, and African-American women have had somewhat <a href="http://theunsilencedscience.blogspot.com/2012/04/racial-amplitudes-of-scholastic.html">improving SAT scores</a> relative to African-American men over time. It might be good to mention alternative cultural explanations, like machismo, male-dominance of underground economy pulling men from educational pursuit, family or community breakdown, post-colonial loss of order, differences in economic structure that favor heavy manual labor, etc. You could integrate this with the brain versus brawn dichotomy, but you could emphasize how your predictions based on evolutionary theory fit the data so well.

I never assumed that. I even included GDP in the partial correlation, with the stated assumption that it will decrease male advantage, thus confounding the relationship. The correlation between sex dimorphism and CPS score is stronger after accounting for GDP. This paper is not a paper about cultural explanations, I'd prefer to stick to biological explanations as there is no way at present of testing the cultural hypotheses and it would go beyond the scope of this study.

Line 11 & 257:
I don't think it is clear to say sexual selection increases the phenotype value. I think it is better to say that sexual selection increases the prevalence of a favored phenotype. Only mutation creates novel phenotypes.

I never claimed that sexual selection creates novel phenotypes. All I said is that the average value for a trait will increase in the presence of selection.

Line 28:
Reserve passive verb tense for avoiding first person.

We had a precented for a reviewer complaining about first person but we decided that this journal will allow the use of first person as more appropriate for scientific discourse.

Line 68:
Intersexual competition would be boys vs. girls.

No. Intersexual competition operates through female choice. Intrasexual competition operates through male-male or female-female competition. Check Wikipedia or any other academic source.

Line 71:
It's debatable whether warriors have high status historically, especially in recent history, so say in antiquity.

The following two statements did not have sources:

Line 71:
"Moreover, men in antiquity performed endeavours such as hunting and making war against other tribes or nations, actions which require greater fluid intelligence and strategic planning, and the best warriors and hunters have traditionally enjoyed a dramatic boost in status, which would have translated into better reproductive success."

Line 102:
"Moreover, since sexual selection operates more strongly on males, a greater reduction in variance should be observed in males than in females."
[T]he average country IQ (estimated from PISA Creative Problem Solving) is positively correlated to sex dimorphism and the latter in turn is inversely correlated to variance in intelligence scores withn populations.

The average country PISA score was positively correlated with absolute sex difference (r= 0.225) albeit not significantly (p= 0.142; N=44).
However, the partial correlation between absolute sex difference and average country score (controlling for GDP) was significant (r=0.344; p= 0.024; N=44).

The correlation between 2000-2009 PISA math and sex differences was r (df=71) = 0.142 ns; for reading r (df=73) = -0.075 ns! I attached my SPSS file and the paper + supplementary file I took the scores from. Why, if national IQs are positively correlated with sexual differences, are they not correlated with math/reading differences. I eyeballed the early 20th century age-heaping data and I didn't see a positive correlation either. File attached. (I don't care to debate whether "PISA Creative Problem Solving" is a better measure of real intelligence than PISA math/reading.) Could you add a GDP variable to my PISA file and see if controlling for it salvages the math/reading correlations? If not, I can't approve -- unless you do some serious explaining.
"This paper is not a paper about cultural explanations, I'd prefer to stick to biological explanations as there is no way at present of testing the cultural hypotheses and it would go beyond the scope of this study."

The GDP discussion is good, but that isn't necessarily the only cultural factor in a whole country. Some people (like feminists) will see your results and believe that cultural factors completely explain them. I'm not saying they would be right, but you have no way to isolate the genetic factors. That doesn't mean you need to write extensively about multiple possible cultural hypotheses, but you could write a short defense for why you think evolutionary factors dominate the results (cite a twins study or GCTA) or add a disclaimer that you don't rule out cultural explanations.

"All I said is that the average value for a trait will increase in the presence of selection."

Phenotypes don't necessarily have a "value," and you were speaking of phenotypes in general. IQ does, but the selection doesn't increase the IQ in a family line. It increases the prevalence of the higher IQ levels (presumably) and shifts the Gaussian curve. This is just an issue of clarity and precision of language, not substance. You kept one of the three changes of this wording that I suggested in the abstract.

"We had a precented for a reviewer complaining about first person but we decided that this journal will allow the use of first person as more appropriate for scientific discourse."

I only meant that you should only use passive verb tense when you have a good reason. I changed the verb, and you kept the change, anyway.

"No. Intersexual competition operates through female choice. Intrasexual competition operates through male-male or female-female competition. Check Wikipedia or any other academic source."

I couldn't find anything on Wikipedia, but I did find a <a href="http://www.ncbi.nlm.nih.gov/pubmed/15612284">pubmed article</a> that agrees with me. Intersexual competition is what it sounds like--competition between males and females.

I still see grammatical errors and the tables don't look very neat. I think it's a good paper, but better presentation and clarity would improve it. I don't know why that journal rejected it, but I imagine they would frown upon citing Wikipedia and Steve Sailer's blog.

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Space after kingdom

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Semicolons not commas after each year to separate studies

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Missing comma after 1998)

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Missing comma after 2005)

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You still have a starting quotation mark without an ending quotation mark.

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Period always before quotation marks.

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I still think you should avoid 's after (1982).

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Non is not a word. Add the hyphen for non-significantly.

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No period.
"I couldn't find anything on Wikipedia, but I did find a <a href="http://www.ncbi.nlm.nih.gov/pubmed/15612284">pubmed article</a> that agrees with me. Intersexual competition is what it sounds like--competition between males and females."

Intersexual competition in the context of sexual selection is absolutely not male/female competition. Here is what Wikipedia says at the "Sexual selection" article: Thus, sexual selection takes two major forms: intersexual selection (also known as 'mate choice' or 'female choice') in which males compete with each other to be chosen by females; and intrasexual selection (also known as 'male–male competition') in which members of the less limited sex (typically males) compete aggressively among themselves for access to the limiting sex.
Apart from Wikipedia, this is basic knowledge. Look, I did my MSc thesis on Sexual Selection and I know what I am talking about. I could cite you tons of papers and articles to support my use of this expression, but it would be like for a mathematician writing in an academic journal having to go back and explain to reviewers high school math. It's a mean job.

I will work on the typos and upload an updated version of the manuscript.
"Here is what Wikipedia says..."

Notice that the source of this passage is just another Wikipedia page in another language. No matter. It looks like we agree to change "intersexual competition" to "intersexual selection." That is a much less confusing term.
[T]he average country IQ (estimated from PISA Creative Problem Solving) is positively correlated to sex dimorphism and the latter in turn is inversely correlated to variance in intelligence scores withn populations.

The average country PISA score was positively correlated with absolute sex difference (r= 0.225) albeit not significantly (p= 0.142; N=44).
However, the partial correlation between absolute sex difference and average country score (controlling for GDP) was significant (r=0.344; p= 0.024; N=44).

The correlation between 2000-2009 PISA math and sex differences was r (df=71) = 0.142 ns; for reading r (df=73) = -0.075 ns! I attached my SPSS file and the paper + supplementary file I took the scores from. Why, if national IQs are positively correlated with sexual differences, are they not correlated with math/reading differences. I eyeballed the early 20th century age-heaping data and I didn't see a positive correlation either. File attached. (I don't care to debate whether "PISA Creative Problem Solving" is a better measure of real intelligence than PISA math/reading.) Could you add a GDP variable to my PISA file and see if controlling for it salvages the math/reading correlations? If not, I can't approve -- unless you do some serious explaining.

I will have a look at the files once I will be able to get my hands on a decent computer (my PC is broken). I have already explained that scholastic achievement is not fluid g. My paper is about sexual selection for fluid g. Reading is the least fluid measure of intelligence you could find, so it's not surprising that you didn't find a correlation. You shouldn't threaten to not approve of my paper. Your approval or not does not make my thesis right or wrong. Don't rush to judgments..you seem thirsty for a decision, like an old style high school teacher who enjoys failing his students. We're just having a discussion here, so chill out. You are using silly measures of intelligence, they're bad proxies, such age heaping data. And you are totally misunderstanding my argument. I never claimed sexual selection explains reading ability or numeracy. They tell you nothing about fluid g. You found a positive correlation between math and sex differences, right? Math is probably the best proxy for fluid g among the measures you chose (although I am afraid it's too school aptitude loaded), although it's not as good as CPS. If you cannot appreciate that scholastic aptitude is not fluid g, then you're welcome to stop reviewing my paper.As I said, your disapproval will not make my hypothesis more or less correct.