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[OQSPS] Inequality across prefectures in Japan is different

#16
Bryan,

Thanks for reviewing.

Adjusting for population size
As you say, this adjustment is exploratory and there was no strong theoretical justification for doing this. For this reason, it is clearly labelled as so in the paper, e.g. I write "However, in an exploratory (unplanned) analysis ...".

The question of what the unit of analysis is (in this case prefectures) and what one is really interested in is a common conundrum for multi-level data analysis. Should we give more importance to results from schools if they have more students? My preference is to weigh units by their importance if possible, while yours seem to be not to do so. Presumably, in a country-level analysis, you would give equal weight to Monaco as you would to the USA despite the latter having about 8500 times as many citizens. Many would probably find that strange. I note that not using weights has been questioned in the cognitive sociology literature (Hunt and Sternberg), so it is (sort of) a case of: damned if I do, damned if I don't.

In this case, the control was not made for population size itself, but for (log) population density (in the final analysis). Population density has (I think) been used as an indicator in other S factor analyses and usually has a positive loading (closely related to urbanity which loads positively). Thus, using it as a control is somewhat strange at least.

However, one could make similar criticism of immigrant % as done in the recently published paper on French departments. http://mankindquarterly.org/archive/paper.php?p=803 (ungated https://www.researchgate.net/publication...ev=prf_pub) Perhaps immigrant % should be seen as another indicator of S, not something to control for. After all, the higher S areas tend to attract more immigrants if one looks at a fairly zoomed-out level (immigrants live in cities, tho in the poor areas). Here I am talking about European style, recent immigration (since about 1970).

I don't offer any particular reason for why one would need to control for population density in Japan, but not other places because I can't think of any such reason. It is quite the mystery. In future S factor studies I will try including controls for population density to see what it does. Perhaps one should do a big meta-analysis. Since I have published all my data from all studies, anyone with the time and competence can do this.

Jensen's method
You are right that the paper is light on this method. I have used it so much that it doesn't seem special to me any more (the curse of knowledge).

I have added a footnote with a brief explanation:

Quote:Jensen's method (method of correlated vectors, named after the great psychologist Arthur Jensen) consists of correlating the factor loadings of indicators with their relationships to some criterion variable. The reasoning is that if the relationship between the factor scores and the criterion variable is real, then (everything else equal) the indicators that have stronger loadings on the factor (i.e. are better measures of it) should be more strongly related to the criterion variable than those with weaker loadings. For more details, see [1], [19].

Data-driven vs. theory-driven research
The difference in methods that you identify concerns one aspect of data-driven research vs. theory-driven research. You suggest using researcher judgment to classify variables into groups and aggregate the results. This however requires that choices be made, choices that could be questioned. I prefer the more agnostic approach. Often, these employment variables were not that strongly correlated, owing to complex definitions of who is and isn't included in the categories. For instance, unemployment might only include those that can work, thus excluding the pensioned and the disabled. Or it might include only those receiving benefits (and thus not housewives/husbands). Combining variables risks missing importance differences between the variables.

Hierarchical extraction
One could use hierarchical extraction of S. In fact I have been experimenting with this but not published much on it. The topic opens up a large number of methodological questions that require quite a bit of work to answer. I have not had the time yet to seriously examine all of them and thus I prefer not to use this approach. It may change in the future.

See, however: http://openpsych.net/forum/showthread.php?tid=264 This paper is mostly a reply to your comments on this topic in another paper (commentary to our target article in Mankind Quarterly; the paper is currently not publicly available).

Causality
One could make a broader factor "well-being" as you did in the 2010 paper (Pesta et al). However, I want to align the integrate the research with that from behavioral genetics and differential psychology looking at the causality from individual differences to educational, economic, criminologic and medical outcomes. The reasoning is that the same general causality that holds in that area holds at the aggregate level: countries, states, communes, departments, prefectures, cities, etc.. This is my working hypothesis, not something that is definitely established.

For this reason I classify S as an outcome variable and cognitive ability as a causal predictor. It is likely that some backwards causation exists for the poorer regions of the world, but most will be forwards (my guess).

Language
The entire paragraph is "A composite dataset was created by merging the two datasets, yielding 63 variables in total. For identification, “_A” and “_B” were added to the variables names, where the first indicates that the data is from Kura and the second that it is from myself.".

This seems grammatical and understandable to me.

References
Hunt, E., & Sternberg, R. J. (2006). Sorry, wrong numbers: An analysis of a study of a correlation between skin color and IQ. Intelligence, 34(2), 131–137. http://doi.org/10.1016/j.intell.2005.04.004

Pesta, B. J., McDaniel, M. A., & Bertsch, S. (2010). Toward an index of well-being for the fifty US states. Intelligence, 38(1), 160-168.

Update
Version 10 (2016-01-30 10:47 AM) has been uploaded to OSF. It features the footnote mentioned above and no other changes.

https://osf.io/zfw38/
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Messages In This Thread
[OQSPS] Inequality across prefectures in Japan is different - by Emil - 2015-Dec-17, 20:39:57
RE: [OQSPS] Inequality across prefectures in Japan is different - by ljzigerell - 2015-Dec-18, 06:40:56
RE: [OQSPS] Inequality across prefectures in Japan is different - by Emil - 2015-Dec-18, 07:43:46
RE: [OQSPS] Inequality across prefectures in Japan is different - by ljzigerell - 2015-Dec-18, 18:38:52
RE: [OQSPS] Inequality across prefectures in Japan is different - by Emil - 2015-Dec-23, 06:06:58
RE: [OQSPS] Inequality across prefectures in Japan is different - by ljzigerell - 2015-Dec-23, 09:31:09
RE: [OQSPS] Inequality across prefectures in Japan is different - by Kenya Kura - 2015-Dec-23, 19:09:56
RE: [OQSPS] Inequality across prefectures in Japan is different - by Kenya Kura - 2015-Dec-21, 17:43:59
RE: [OQSPS] Inequality across prefectures in Japan is different - by Emil - 2015-Dec-23, 11:17:58
RE: [OQSPS] Inequality across prefectures in Japan is different - by Emil - 2015-Dec-23, 15:57:40
RE: [OQSPS] Inequality across prefectures in Japan is different - by Emil - 2015-Dec-23, 23:05:40
Proofreading - by Emil - 2015-Dec-27, 22:08:17
RE: [OQSPS] Inequality across prefectures in Japan is different - by bpesta22 - 2016-Jan-25, 18:27:51
RE: [OQSPS] Inequality across prefectures in Japan is different - by Emil - 2016-Jan-25, 22:23:50
RE: [OQSPS] Inequality across prefectures in Japan is different - by bpesta22 - 2016-Jan-29, 19:56:06
Reply to Pesta - by Emil - 2016-Jan-30, 11:50:54
RE: [OQSPS] Inequality across prefectures in Japan is different - by NoahCarl - 2016-Apr-04, 16:44:02
RE: [OQSPS] Inequality across prefectures in Japan is different - by Emil - 2016-Apr-05, 23:29:41
RE: [OQSPS] Inequality across prefectures in Japan is different - by NoahCarl - 2016-Apr-06, 12:00:22
RE: [OQSPS] Inequality across prefectures in Japan is different - by Emil - 2016-Apr-06, 19:18:35
 
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