2014-Oct-06, 20:57:19

Quote:The aim of this article is to provide an update to Huang & Hauser (2001) study

This should be: Huang & Hauser's (2001)

Quote:The wordsum correlates at 0.71 with the AGCT aptitude test, and that the wordsum has an internal consistency reliability of 0.71 for whites and 0.63 for blacks (Huang & Hauser, 2001), which is not surprising given the shortness of the test.

This should be: The wordsum correlates at 0.71 with the AGCT aptitude test, and it has an internal reliability of 0.71 for whites and 0.63 for blacks (Huang & Hauser, 2001); these reliabilities are relatively low for cognitive measures, but this is not supprising given the shortness of the test.

Quote:The usual operation

This should be: formula.

Quote:But it is clear that the d gaps in the period 1988-1993 were clearly smaller than than earlier years. Lynn has also regressed the d gaps on years. The "b" slope was -0.004, which means that over 22 years, the d gap has been reduced by 0.004*22=0.088, given that the linearity assumption holds (which was true according to Lynn). This is indeed not very large.

Try: But it is clear that the d gaps in the period 1988-1993 were smaller than than earlier years. Lynn has also regressed the d gaps on years. The "b" slope was -0.004, which means that, over 22 years, the d gap diminished by 0.004*22=0.088, given that a linearity assumption holds (which was true according to Lynn). This is indeed not very large.[/quote]

Quote:However, their d scores differ from Lynn's only for years 1993 and 1994. But, more importantly, they faulted Lynn for not having used cohort as the variable of time trend (which can be calculated as year minus age).

Try: However, their d scores differ from Lynn's only for years 1993 and 1994. But, more importantly, they faulted Lynn for not having used cohort as the variable for the time trend (which can be calculated as year minus age).

Quote:Here is an explanation of the two concepts. With survey year, assuming age is held constant, we are asking how are the 40-year-olds in 1980 different from the 40-year-olds in 1990. The former experienced WWII, but the latter didn't. This is the period effect. With birth cohort, assuming age is held constant, we are asking how are people born in 1950 different from people born in 1960, when they were both 40 years old. The former experienced the sexual revolution in their teenage years, but the latter didn't. This is the cohort effect. The two effects may or may not be the same thing. (I must thank Satoshi Kanazawa for the tip.)

Try: Here is an explanation of the two concepts: With survey year, assuming age is held constant, we are asking, "How are the 40-year-olds in 1980 different from the 40-year-olds in 1990?". The former experienced WWII, but the latter didn't. This is the period effect. With birth cohort, assuming age is held constant, we are asking, "How are 40 year olds born in 1950 different from 40 year olds born in 1960?". The former experienced the sexual revolution in their teenage years, but the latter didn't. This is the cohort effect. The two effects may or may not be the same thing. (I must thank Satoshi Kanazawa for the tip.)

Quote:Given their parameters of 2.641 for intercept, 3.037 for race, 0.024 for the slope of year, and -0.0176 for the interaction, we can predict the changes in the gap over time. This is done by computing the white trend with race*year interaction, 2.641+3.037+(0.024*24)-(0.0176*24)=5.8316, and the white trend without the interaction, 2.641+3.037+(0.024*24)=6.2540, which gives a difference of 0.4224

It's standard to round to the same level of significant digits when dealing with the same sets of numbers. So either 0.024 and -0.018 or 0.024? and -0.0176.

Quote:difference (corrected for censored distribution of wordsum)

What does this mean? Also, add an article ("the") before censored.

Quote:Squared and perhaps cubed terms should have been applied to categorical variables of years and their interaction with race rather than using the continuous variable of survey year.

Why "should" have they? Was the relations non-linear. Perhaps you mean:

The authors should have checked if using squared and perhaps cubed terms produced a better fitting model. Doing so, might have generated different results.

The finding of Huang & Hauser (2001) is interesting because it is known that the black-white IQ gap in the U.S. has not declined in the adult samples, only in the children samples (Rushton & Jensen, 2006; Dickens & Flynn, 2006).

Maybe: The finding of Huang & Hauser (2001) is interesting because it is known that the black-white IQ gap in the U.S. has not declined in adult samples but only in child and adolescent ones (Rushton & Jensen, 2006; Dickens & Flynn, 2006).

(Use "the adult samples" when referring to a specific set of samples; use "adult samples" when referring to an unspecific set of samples; in this case, I think you are referring to an unspecific set. If not, you should say e.g.,:

It is known that the black-white IQ gap in the U.S. has not declined in the adult samples but only in the child samples discussed by Rushton & Jensen (2006) and Dickens & Flynn (2006).

Quote: It is possible, nonetheless, that there was a gap closing before the period analyzed by Dickens and Flynn. See Murray (2007).

Try: It is possible, nonetheless, that there was a gap closing before the period analyzed by Dickens and Flynn (see Murray, 2007).

Quote:Before deciding which method to apply, one needs to examine the distribution of the variables we will use.

Try: Before deciding which method to apply, one needs to examine the distribution of the variables one wishes to use.

Quote:An important assumption of linear regression is the normality of the data, especially the distribution of the dependent variable.

Try: An important assumption of linear regression is the normality of the data, especially in context to the distribution of the dependent variable.

Quote:The right procedure should be to use a tobit regression (for an introduction, see, McDonald & Moffitt, 1980).

Try: The right procedure should be to use a tobit regression (for an introduction, see McDonald & Moffitt, 1980).

Quote:Since the year 2000, the GSS begins to ask whether

Try: Since the year 2000, the GSS began to ask whether

Quote:For respondents in survey year 2000+ I have only included the respondents who declared not being hispanic (see appendix).

Use a common.

Quote:The variable cohort has values going from 1883 to 1994. The variable sex has the following values; male=1, female=2. The variable age has values going from 18 to 89. The variable degree has the following values; 0=lower than high school, 1=high school, 2=junior college, 3=bachelor, 4=graduate. The variable educ has values going from 0 to 20. The variable realinc has values going from 245 to 162607, and the respective numbers for log income are 5.5 and 11.99. The variable reg16 has the

For clarity place the variable names in quotes.

The variable "cohort" has values going from 1883 to 1994. The variable "sex" has the following values; male=1, female=2. The variable "age"....

Quote:According to the GSS codebook, the "white" category in variable "race" (before the year 2000) includes mexicans, spaniards and puerto ricans "who appear to be white".

Capitalize e.g., Mexican.

Quote:As for age variable, I decided to remove (set to missing data) people aged 70 or more

Try: As for the age variable...

Quote:Hence, following the recommendations of Hauser & Huang (1999) I weight the data by the variable "weight" which is the interaction of the variables "wtssall" and "oversamp", although this will not change the results.

I would use a comma.

Quote:The black-white raw score gap in cohort1 was 2.023 items correct and has become 1.001 item correct in cohort6, which means the gap has been reduced by an half, while the gap was 1.638 items correct in year1 and has become 1.333

Quote:This is because the more recent cohorts are younger, and the wordsum correlates positively with age (r=0.1005). In models 3 and 4, the scores among whites have a declining trend.

Who ever reported correlations to the ten-thousandth place? Also try:

This is because the more recent cohorts are younger, and wordsum correlates positively with age (r=0.1005). In models 3 and 4, the scores among whites have a declining trend.

Quote:This is still 50% reduction

Try: This is still a 50% reduction

Quote:A subsequent analysis is done by computing the d gap (see supplementary file) within each of the category of the dummy variables.

Categories.

Quote:I split the variable wordsum into two parts

Try: I split the variable "wordsum" into two parts

Quote:Another way to investigate whether or not the improvement occurs at high levels is to conduct logistic regression with wordsum as dependent binary variable (score levels 0-7 coded 0 and score levels 8-10 coded 1)

Try: Another way to investigate whether or not the improvement occurs at high levels is to conduct logistic regression with wordsum as the dependent binary variable (score levels 0-7 coded as 0 and score levels 8-10 coded as 1)

Quote:The most notable problem with the wordsum is not to be a measure of general intelligence

Try: The most notable problem with using wordsum, in this context, is that it is not a great measure of general intelligence.

Quote:Given Huang & Hauser's (1996, pp. 7-8) discussion, there is no clear answer to this question

Try: Given Huang & Hauser's (1996, pp. 7-8) discussion, there is no clear way to determine if this has occurred.

Quote:The affirmation that the test has become harder may be true. To some extent

Try: The affirmation that the test has become harder may be true to some extent.

Quote:whites find the wordsum harder over time while the blacks would find it a little bit easier

try: whites find the wordsum harder over time while the blacks find it a little bit easier

Quote:Generally, there is some indication that the black-white gap has been under-estimated in early cohorts. And by the same token, the magnitude of the gap narrowing.

Fragment. Try: Generally, there is some indication that the black-white gap has been under-estimated in early cohorts -- and by the same token, the magnitude of the gap narrowing.

Quote:But at the same time, the white trend could have been even flatter or turned out to be somewhat dysgenic.

I don't understand this and I would advise against using "dysgenic", since this implies a causal model, the discussion of which is outside the scope of the paper. Maybe just delete the sentence.

Quote:Granted the limitation of the wordsum test, one may wonder what is the consequence of the black-white gap decline for the genetic hypothesis proposed by Rushton & Jensen (2010). ...

I wouldn't, in this paper, discuss this. It's not directly relevant to the topic of the paper and it unnecessarily geneticizes the discussion (thus turning off potential readers). I've made the same point regarding many of Emil's discussions: Don't conflate issues e.g., the "spatial transferability hypothesis" with certain global genetic hypotheses. Delete the whole paragraph.

I'll get back to you regarding method later.