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[ODP]Putting Spearman’s Hypothesis to Work: Job IQ as a Predictor of Employee Racial

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Bryan,

Quotes are yours unless otherwise specified.

Quote:REPLY: We did not cross-check jobs, but instead relied on the Wonderlic’s ability and expertise at generating estimated IQs for different jobs. Also, we didn’t have older Wonderlic data, and suspect—as you point out—that matching jobs might be frustrating.

Older Wonderlic data is given by Gottfredson's classic 1997 paper. It was in my link.

Old Wonderlic data from Gottfredson.

Quote:REPLY: Would it be ok to include “(but, see, <your link>)” immediately after the word “version” in our quote above? If not, we can delete this entire section.

No. Please see the discussion about your previous submission. The BDS does not have twice the g-loading of FDS. Dalliard and myself compiled several studies to show this, yet you made the same exact claim in your next submission. I find that odd.

Emil, previously Wrote:This (the slightly higher mean IQ among the occupations) corresponds to the low correlation found between being out of a job and IQ at the individual level. You could back-estimate this correlation using this mean. Just a minor check.


Quote:REPLY: Not sure how to do this. If desired for our paper, could you please advise?

One could use a simple cutoff based model, which assumes that everybody above a certain cutoff are in work and everybody below is not. One could also use a more gradual change, but I didn't have a ready made function for this.

These are aggregated data, so one should use the weighted mean IQ, weighted by occupation population. These are not given in your datafile, so I could not do this.

I tried with the given number, but this produced a correlation of .67, which is much too strong. So my proposed method doesn't work. Just ignore this.

(code for this is found in my R code)

Emil, previously Wrote:It would be better to just average the BLS values across years, no?


Quote:REPLY: Correlations seem more intuitive? The rank ordering of jobs by ethnic composition is pretty much the same across a two year span.

You misunderstood. I proposed that you use the average of the BLS 2014 and 2012 values to remove some of the slight 'measurement error'.

I did this in my replication.

Quote:REPLY: In addition to your hypotheses, we wonder about a potential floor effect on the percentage of Asians in each job. We’d prefer not to complicate the manuscript by addressing why the %Asian correlation was lower than might be expected (it was nonetheless non-trivial and significant). This might be an interesting question for an additional study, but the present study just predicted a significant/non-zero correlation between %Asian and IQ. Although the correlation was smallish, its existence was predicted by Spearman’s hypothesis (and testing this hypothesis was the purpose of our study). Also, since our data are just for the USA, wouldn’t a group six points above average IQ produce smaller over/under-representation relative to a group 15 points below average IQ?

1)
Not controlling for known confounds (interests in this case) which you already have the data for is not really defensible. After all, you are interested in the effect of cognitive ability itself, not whatever it is that it happens to be correlated with. If you use correlations, you will get a confounded estimate of the influence of cognitive ability itself.

2)
Merely looking for p < alpha vs. p > alpha results is not a good way of doing science. What matters is whether the numbers fit in size. Please see: http://www.phil.vt.edu/dmayo/personal_we...esting.pdf

3)
By your reasoning, White% should produce the weakest correlation, yet it does not.

Quote:REPLY: Our correlational values are effect sizes, we think. Schmidt and Hunter’s paper was a meta-analysis and so reported effect sizes. Beyond reporting correlations, I’m not sure that Gottfredson calculated effect sizes. If I’m misinterpreting what you’re asking for here, please let me know.

Your correlations are effect sizes, yes. However, I asked for "the effect sizes of the prior research so readers can see whether the effect sizes are similar".

You present some new results. What the readers need to know is whether they fit in size with the previous results. For instance, if you find r = .20 and previous studies have found r = .95, something is wrong somewhere.

The data variable (complexity) was correlated with mean IQ at .86 in your study. You cite:

Gottfredson, L. S. (1986). Occupational aptitude patterns map: Development and implications for a theory of job aptitude requirements (Monograph). Journal of Vocational Behavior, 29, 254-291.

Gottfredson, L. S. (2003). g, jobs, and life. In H. Nyborg (Ed.), The scientific study of general intelligence: Tribute to Arthur R. Jensen (pp. 293-342). New York: Pergamon.

However, I could not find any complexity x mean IQ correlation in these papers. She does give job mean IQs and presents factor analysis results of job attributes, but does not appear to actually correlate them. Maybe I missed the number somewhere?

--

Data analysis
I replicated the authors' analysis and also did the required additional multiple regression analyses. I furthermore did some path models too, which allow for more precise causal modeling.

I used the average race% values from the BLS (2012 and 2014) to increase reliability. This results in the following correlations:

Code:
iq white black asian other  data people things
iq      1.00  0.48 -0.61  0.23 -0.51 -0.86  -0.53   0.04
white   0.48  1.00 -0.85 -0.38 -0.49 -0.52  -0.37  -0.04
black  -0.61 -0.85  1.00 -0.14  0.47  0.66   0.30   0.09
asian   0.23 -0.38 -0.14  1.00 -0.14 -0.21   0.13  -0.07
other  -0.51 -0.49  0.47 -0.14  1.00  0.45   0.24  -0.04
data   -0.86 -0.52  0.66 -0.21  0.45  1.00   0.50  -0.01
people -0.53 -0.37  0.30  0.13  0.24  0.50   1.00  -0.24
things  0.04 -0.04  0.09 -0.07 -0.04 -0.01  -0.24   1.00


Note that I have included "other", which is the residual group. This is some mix of Native Americans, Hispanics, mixed race persons and so on. The mean IQ of this group is usually found to be somewhat below the population mean (around 95), so one would expect a negative correlation, which is also found.

John prefers the rationized group proportions (for the lack of a better term). In this way the influence of the "other" group is removed. So, for Whites this is simply White% / (White% + Black% + Asian%). Same for the others. These correlations are:

Code:
iq white_ratio black_ratio asian_ratio  data people things
iq           1.00        0.44       -0.61        0.22 -0.86  -0.53   0.04
white_ratio  0.44        1.00       -0.84       -0.42 -0.49  -0.35  -0.04
black_ratio -0.61       -0.84        1.00       -0.14  0.66   0.30   0.09
asian_ratio  0.22       -0.42       -0.14        1.00 -0.20   0.13  -0.07
data        -0.86       -0.49        0.66       -0.20  1.00   0.50  -0.01
people      -0.53       -0.35        0.30        0.13  0.50   1.00  -0.24
things       0.04       -0.04        0.09       -0.07 -0.01  -0.24   1.00


So this correction made little difference and seems unnecessary.

Of more interest are multiple regressions where we take the other job data into account. I used cognitive ability, people and things to predict each of the race%.

For Whites:

Code:
$coefs
        Beta   SE CI.lower CI.upper
iq      0.39 0.09     0.20     0.57
people -0.19 0.10    -0.37     0.00
things -0.09 0.08    -0.26     0.07

$meta
            N            R2       R2 adj. R2 10-fold cv
       124.00          0.26          0.24          0.19


Blacks:

Code:
$coefs
        Beta   SE CI.lower CI.upper
iq     -0.60 0.09    -0.77    -0.43
people  0.02 0.09    -0.16     0.19
things  0.12 0.07    -0.03     0.26

$meta
            N            R2       R2 adj. R2 10-fold cv
       124.00          0.38          0.36          0.34


Asians:

Code:
$coefs
       Beta   SE CI.lower CI.upper
iq     0.41 0.10     0.21     0.61
people 0.34 0.10     0.14     0.55
things 0.00 0.09    -0.17     0.17

$meta
            N            R2       R2 adj. R2 10-fold cv
       124.00          0.14          0.12          0.03


Notice the very low cross-validated R2. This is suspicious.

Code:
$coefs
        Beta   SE CI.lower CI.upper
iq     -0.54 0.09    -0.72    -0.36
people -0.05 0.10    -0.24     0.14
things -0.03 0.08    -0.19     0.13

$meta
            N            R2       R2 adj. R2 10-fold cv
       124.00          0.27          0.25          0.24


So, to recap, the standardized betas for the races with the other job predictors were:
White: .39
Black: -.60
Asian: .41
Other: -.54

Thus, the Asian result is not really an outlier once one takes into account their higher preference for working with people (people beta = .34). Note that White has a people beta at -.19, but it's not a reliable finding (cf. the confidence interval). Still, this means that Whites and Asians are pretty different on this preference, apparently.

Path models
Here one can stipulate the causal order of variables (kind of). I specified that the interests are caused by cognitive ability and that the race% are caused jointly by cognitive ability requirement and interests.

Here's the plots:

White:
   

Black:
   

Asian:
   

Other:
   

Looking at these we see that the results for the cognitive ability paths are consistent with the other results. Direct paths: .38, -.51, .23, -.51. For Asian and White there are opposite direction indirect paths thru the people interest as seen before.

--

Code for my replication is in the OSF folder "Emil_replication".

https://osf.io/pxmjc/files/
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Messages In This Thread
[ODP]Putting Spearman’s Hypothesis to Work: Job IQ as a Predictor of Employee Racial - by bpesta22 - 2016-May-23, 02:44:35
Review - by Emil - 2016-May-23, 16:03:27
RE: [ODP]Putting Spearman’s Hypothesis to Work: Job IQ as a Predictor of Employee Racial - by bpesta22 - 2016-May-30, 16:44:17
RE: [ODP]Putting Spearman’s Hypothesis to Work: Job IQ as a Predictor of Employee Racial - by bpesta22 - 2016-May-24, 13:06:23
RE: [ODP]Putting Spearman’s Hypothesis to Work: Job IQ as a Predictor of Employee Racial - by Emil - 2016-May-24, 17:42:42
re - by Chuck - 2016-May-25, 00:41:14
RE: [ODP]Putting Spearman’s Hypothesis to Work: Job IQ as a Predictor of Employee Racial - by bpesta22 - 2016-May-30, 18:14:59
RE - by Chuck - 2016-May-30, 21:37:35
RE: [ODP]Putting Spearman’s Hypothesis to Work - by Meng Hu - 2016-Jul-07, 01:09:07
RE: [ODP]Putting Spearman’s Hy - by bpesta22 - 2016-Jul-07, 02:10:01
RE: [ODP]Putting Spearman’s Hypothesis to Work: Job IQ as a Predictor of Employee Racial - by Emil - 2016-May-30, 23:33:03
RE: [ODP]Putting Spearman’s Hypothesis to Work: Job IQ as a Predictor of Employee Racial - by Chuck - 2016-May-31, 00:49:59
RE: [ODP]Putting Spearman’s Hypothesis to Work: Job IQ as a Predictor of Employee Racial - by Emil - 2016-Jun-01, 22:59:27
RE: [ODP]Putting Spearman’s Hypothesis to Work: Job IQ as a Predictor of Employee Racial - by bpesta22 - 2016-May-31, 12:49:31
RE: [ODP]Putting Spearman’s Hypothesis to Work: Job IQ as a Predictor of Employee Racial - by Chuck - 2016-Jun-01, 07:40:31
RE: [ODP]Putting Spearman’s Hypothesis to Work: Job IQ as a Predictor of Employee Racial - by Emil - 2016-Jun-01, 10:46:09
RE: - by Chuck - 2016-Jun-01, 22:58:44
Review #2 - by Emil - 2016-Jun-02, 00:54:25
RE: [ODP]Putting Spearman’s Hypothesis to Work: Job IQ as a Predictor of Employee Racial - by bpesta22 - 2016-Jun-02, 03:58:29
RE: [ODP]Putting Spearman’s Hypothesis to Work: Job IQ as a Predictor of Employee Racial - by Chuck - 2016-Jun-02, 04:30:19
RE: [ODP]Putting Spearman’s Hypo - by bpesta22 - 2016-Jun-05, 02:35:40
RE: [ODP]Putting Spearman’s Hypothesis to Work: Job IQ as a Predictor of Employee Racial - by Chuck - 2016-Jun-05, 02:53:00
RE: [ODP]Putting Spearman’s Hypothesis to Work: Job IQ as a Predictor of Employee Racial - by Emil - 2016-Jun-02, 09:50:08
RE: [ODP]Putting Spearman’s Hypoth - by bpesta22 - 2016-Jun-05, 02:56:14
Reply to Bryan - by Emil - 2016-Jun-08, 15:27:47
RE: [ODP]Putting Spearman’s Hypothesis to Work: Job IQ as a Predictor of Employee Racial - by Chuck - 2016-Jun-09, 20:55:49
RE: [ODP]Putting Spearman’s Hypo - by bpesta22 - 2016-Jun-10, 14:14:24
RE: [ODP]Putting Spearman’s Hypothesis to Work: Job IQ as a Predictor of Employee Racial - by Emil - 2016-Jun-10, 18:29:06
RE: [ODP]Putting Spearman’s Hypothesis to Work: Job IQ as a Predictor of Employee Racial - by bpesta22 - 2016-Jun-12, 03:18:52
RE: [ODP]Putting Spearman’s Hypot - by bpesta22 - 2016-Jun-12, 15:49:12
RE: [ODP]Putting Spearman’s Hypothesis to Work: Job IQ as a Predictor of Employee Racial - by Emil - 2016-Jun-12, 23:33:38
RE: [ODP]Putting Spearman’s H - by bpesta22 - 2016-Jun-16, 02:57:40
RE: [ODP]Putting Spear - by bpesta22 - 2016-Jun-29, 05:16:16
RE: [ODP]Putting Spearman’s Hypothesis to Work: Job IQ as a Predictor of Employee Racial - by Meng Hu - 2016-Jul-01, 00:37:07
RE: [ODP]Putting Spearman’s Hypothesis to Work: Job IQ as a Predictor of Employee Racial - by Emil - 2016-Jun-29, 21:41:37
RE: [ODP]Putting Spearman’s Hypothesis to Work: Job IQ as a Predictor of Employee Racial - by Emil - 2016-Jul-04, 04:29:07
RE: [ODP]Putting Spearman’s - by bpesta22 - 2016-Jul-04, 23:01:17
SH - by Emil - 2016-Jul-05, 02:32:14
RE: [ODP]Putting Spearman’s - by bpesta22 - 2016-Jul-05, 03:37:10
RE: [ODP]Putting Spearman’s Hypothesis to Work: Job IQ as a Predictor of Employee Racial - by Chuck - 2016-Jul-05, 20:05:54
RE: [ODP]Putting Spearman’s Hypothesis to Work: Job IQ as a Predictor of Employee Racial - by Emil - 2016-Jul-05, 12:36:29
RE: [ODP]Putting Spearman’s Hypothesis to Work: Job IQ as a Predictor of Employee Racial - by Dalliard - 2016-Jul-07, 23:15:50
RE: [ODP]Putting Spearman’s Hypothesis to Work: Job IQ as a Predictor of Employee Racial - by Meng Hu - 2016-Jul-09, 15:32:42
RE: [ODP]Putting Spearman’s Hypothes - by bpesta22 - 2016-Jul-10, 03:09:05
RE: [ODP]Putting Spearman’s Hypothesis to Work: Job IQ as a Predictor of Employee Racial - by Meng Hu - 2016-Jul-10, 14:17:06
RE: [ODP]Putting Spearman’s Hypothesis to Work: Job IQ as a Predictor of Employee Racial - by Dalliard - 2016-Jul-10, 17:23:57
RE: [ODP]Putting Spearman’s Hypothesis to Work: Job IQ as a Predictor of Employee Racial - by bpesta22 - 2016-Jul-10, 19:44:19
RE: [ODP]Putting Spearman’s Hypothesis to Work: Job IQ as a Predictor of Employee Racial - by Emil - 2016-Jul-11, 10:30:01
RE: [ODP]Putting Spearman’s Hypothesis to Work: Job IQ as a Predictor of Employee Racial - by Dalliard - 2016-Jul-11, 22:26:09
RE: [ODP]Putting Spearman’s Hypothesis to Work: Job IQ as a Predictor of Employee Racial - by Emil - 2016-Jul-12, 09:51:00
RE: [ODP]Putting Spearman’s Hypothesis to Work: Job IQ as a Predictor of Employee Racial - by bpesta22 - 2016-Jul-14, 03:44:14
Publication - by Emil - 2016-Jul-20, 00:10:18
RE: [ODP]Putting Spearman’s Hypothesis to Work: Job IQ as a Predictor of Employee Racial - by bpesta22 - 2016-Jul-20, 04:51:17
RE: [ODP]Putting Spearman’s Hypothesis to Work: Job IQ as a Predictor of Employee Racial - by Emil - 2016-Jul-23, 15:06:26
Historical precedents - by Emil - 2016-Jul-27, 04:19:55
 
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