[OQSPS] Some new methods for exploratory factor analysis of socioeconomic d
2016-Oct-05, 18:09:57, (This post was last modified: 2016-Oct-05, 18:11:07 by Duxide.)
#11
RE: [OQSPS] Some new methods for exploratory factor analysis of socioeconomic d
Revision is OK but there are some standing issues.
I have doubts regarding this sentence: "This means that when a single factor is extracted, all the factor loadings are positive".
Is that so? If so, please provide references. Not necessarily all cognitive tests load positively. For example, reaction time can load negatively when used in a battery since longer RT is associated with lower g. Perhaps you're not referring to ALL cognitive tasks but only IQ tests.

"The purpose of this paper is to review and introduce a number of new methods that were invented for the factor analysis of socioeconomic data.Some of these were presented in various earlier papers and some are new."
This sentence is a bit sloppy. I'd write: The purpose of this paper is to review methods presented in earlier papers and to introduce new ones that were developed for the factor analysis of socioeconomic data".

"new methods that were invented for the factor analysis of socioeconomic data". I would use "developed" instead of invented.

"Some of these were presented in various earlier papers and some are new". Accordingly, delete this and specify which methods were presented in the earlier papers and the new ones.
Please provide references for each method.
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2016-Oct-07, 04:55:25, (This post was last modified: 2016-Oct-07, 04:55:32 by Emil.)
#12
RE: [OQSPS] Some new methods for exploratory factor analysis of socioeconomic d
Forgot to say. I read this and am working on a revision.
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2016-Oct-10, 06:27:12, (This post was last modified: 2016-Oct-10, 06:28:08 by Emil.)
#13
RE: [OQSPS] Some new methods for exploratory factor analysis of socioeconomic d
(2016-Oct-05, 18:09:57)Duxide Wrote: Revision is OK but there are some standing issues.
I have doubts regarding this sentence: "This means that when a single factor is extracted, all the factor loadings are positive".
Is that so? If so, please provide references. Not necessarily all cognitive tests load positively. For example, reaction time can load negatively when used in a battery since longer RT is associated with lower g. Perhaps you're not referring to ALL cognitive tasks but only IQ tests.

Often they reverse the reaction time data, so to preserve the positive manifold. This is easy to do because cognitive test items by definition (Jensen's) must have an agreed upon better performance direction. For reaction time tests, shorter = better, so they are sometimes reversed. I checked a few papers on Google and most of them did not reverse the tests. I have changed the wording a bit and added a footnote explaining this exception.

Quote:"The purpose of this paper is to review and introduce a number of new methods that were invented for the factor analysis of socioeconomic data.Some of these were presented in various earlier papers and some are new."
This sentence is a bit sloppy. I'd write: The purpose of this paper is to review methods presented in earlier papers and to introduce new ones that were developed for the factor analysis of socioeconomic data".

Fair enough.

Quote:"new methods that were invented for the factor analysis of socioeconomic data". I would use "developed" instead of invented.

Yes, that's better.

Quote:"Some of these were presented in various earlier papers and some are new". Accordingly, delete this and specify which methods were presented in the earlier papers and the new ones.
Please provide references for each method.

For each section, I have inserted a sentence in parentheses in the beginning if the method has been used in a previous paper.

--

Updated files on OSF.
https://osf.io/3npj8/files/
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2016-Oct-10, 09:13:47,
#14
RE: [OQSPS] Some new methods for exploratory factor analysis of socioeconomic d
The paper has been considerably improved. I approve publication.
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2016-Nov-01, 00:22:48, (This post was last modified: 2016-Nov-01, 00:23:46 by NoahCarl.)
#15
RE: [OQSPS] Some new methods for exploratory factor analysis of socioeconomic d
Good paper, overall. Some comments/suggestions:

1. Full stop needed on p. 2: "the factor analysis of socioeconomic data Some of these were presented..."

2. Word repeated on p. 3: "related related to the g factor, but to other parts of the variance..."

3. "One problem with this is that the Jensen coefficient (the resulting correlation from applying the method) is sensitive to whether there are variables with negative loadings or not [...] A simple solution is to recode the variables such that higher values correspond to desirable outcomes. This works well in many cases, but not all." (p. 3).

Couldn't one, as a matter of methodology, just take the absolute value (modulus) of the loading, rather than bothering to recode variables?

4. "Such patterns are often seen for cases that consist mostly of one large city (Kirkegaard, 2015e)" (p. 7).

Perhaps cite Carl (2015) here as well, given that it was noted in his original analysis of UK regions that London qualified as such an outlier:

"The correlations were estimated with and without London because in a number of cases, particularly the associations with log weekly earnings and log gross value added (GVA) per capita, London was a clear outlier. This should not be surprising given that London is a large capital city, whereas all the other regions encompass both urban and rural areas."

5. "In the meanwhile, we might try". (p. 13).

In English, one says either "In the meantime..." or "Meanwhile...", not "In the meanwhile".

6. Unnecessary "from" on p. 17: "it does not matter whether scores are derived from using unit weights".

7. Please justify the text.

8. In Section 3, please include a bit more discussion (e.g., a couple of sentences) of which of the proposed methods is to be preferred, particularly in relation to the analysis you perform. I have to say, the second metric––"change in factor size"––seems to me to be the most intuitive. 

9. Also in Section 3, might one consider some kind of cluster analysis (e.g., based on Euclidean distance) to identify outlying cases?
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2016-Nov-01, 00:27:24,
#16
RE: [OQSPS] Some new methods for exploratory factor analysis of socioeconomic d
Thanks for the review. I will work on a revision.
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2016-Nov-02, 20:12:51, (This post was last modified: 2016-Nov-02, 20:16:00 by Emil.)
#17
RE: [OQSPS] Some new methods for exploratory factor analysis of socioeconomic d
Noah,


Quote:1. Full stop needed on p. 2: "the factor analysis of socioeconomic data Some of these were presented..."


Fixed.

Quote:2. Word repeated on p. 3: "related related to the g factor, but to other parts of the variance..."

Fixed.

Quote:3. "One problem with this is that the Jensen coefficient (the resulting correlation from applying the method) is sensitive to whether there are variables with negative loadings or not [...] A simple solution is to recode the variables such that higher values correspond to desirable outcomes. This works well in many cases, but not all." (p. 3).

Couldn't one, as a matter of methodology, just take the absolute value (modulus) of the loading, rather than bothering to recode variables?

This is what is done. But recall that one also has to reverse the indicators if one reverses the loading. Otherwise, the direction of association changes.

Quote:4. "Such patterns are often seen for cases that consist mostly of one large city (Kirkegaard, 2015e)" (p. 7).

Perhaps cite Carl (2015) here as well, given that it was noted in his original analysis of UK regions that London qualified as such an outlier:

"The correlations were estimated with and without London because in a number of cases, particularly the associations with log weekly earnings and log gross value added (GVA) per capita, London was a clear outlier. This should not be surprising given that London is a large capital city, whereas all the other regions encompass both urban and rural areas."

Yes, appropriate to cite the primary study too. Done.

Quote:5. "In the meanwhile, we might try". (p. 13).

In English, one says either "In the meantime..." or "Meanwhile...", not "In the meanwhile".

Fixed.

Quote:6. Unnecessary "from" on p. 17: "it does not matter whether scores are derived from using unit weights".

Fixed.

Quote:7. Please justify the text.

I hate that. No thanks. But Julius will typeset/prettify the paper.

Quote:8. In Section 3, please include a bit more discussion (e.g., a couple of sentences) of which of the proposed methods is to be preferred, particularly in relation to the analysis you perform. I have to say, the second metric––"change in factor size"––seems to me to be the most intuitive.

I have added a new subsection, 3.3:

Conceptually, the metrics are somewhat distinct, so depending on the goal of the analysis, a particular metric may be the best suited for the task. But if the goal is to identify structural outliers in general, it's not clear which one is to be preferred. My current practice is using all of them and then comparing their results. Sometimes, one indicator may give divergent results and so one has to pay extra attention to see if one can figure out why. A general approach is to factor analyze the indicators to get a single structural outlierness score for each case. When doing this, it's important to choose only one of the variants of a given metric. E.g. do not use both mean and maximum absolute loading change, pick one of them.

Lastly, a nice feature of the mean absolute residuals method is that it allows one to see which indicators cause a given case to be a structural outlier. The other methods do not allow for this possibility.


Quote:9. Also in Section 3, might one consider some kind of cluster analysis (e.g., based on Euclidean distance) to identify outlying cases?

Cluster analysis and other classification methods try to classify cases into groups. I don't see how one could use this for measuring structural outlierliness as a continuous variable.

However, it did give me an idea. It's possible to use cluster analysis on the residuals for each case (those computed as part of the MAR method). This would allow one to see if there are clusters in the way cases fail to be predicted by the summary score(s). This could be interesting, but it's not something I've tried yet.

--

Files updated.
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2016-Nov-03, 00:58:33,
#18
RE: [OQSPS] Some new methods for exploratory factor analysis of socioeconomic d
I approve the paper for publication.
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2016-Nov-08, 01:06:31,
#19
RE: [OQSPS] Some new methods for exploratory factor analysis of socioeconomic d
Published.

https://openpsych.net/paper/47
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