Successfully dealing with faking on a self-report personality test

Faking on self-report personality tests is common and a strong drawback of such tests. Many approaches have been tried to counteract this serious source of error, see e.g. a recent papers in the Journal of Applied Psychology (Bangerter, Roulin, & König, 2012; Fan, et al., 2012).

The UPP test (Sjöberg, 2010/2012) is a self-report personality test and as such it is vulnerable to faking in high-stakes testing situations. However, this test uses a simple but powerful methodology for correcting test scores for faking. It measures separately two social desirability (SD) dimensions, one overt (similar to the classical Crowne-Marlowe scale (Crowne & Marlowe, 1960)) and one covert. The covert scale uses items similar to conventional personality items but selected for their strong correlation with the overt scale. The two scales are highly correlated and give similar results when used to correct test scales for faking.

The correction procedure uses regression models where each test scale in turn is the dependent variable and the SD scales are independent variables. It is necessary to fit a new model for each test scale because the different scales are related to SD in different ways, correlations varying widely. The corrected test scales are the residuals in these regression models.

This procedure gives corrected test scales which correlate zero with SD. So far, so good, but does it also work? In other words, can it be validated on empirical data? One way to validated it is to study groups tested under different levels of involvement, from incumbents where test results have no consequences, to applicants where they do, and consequences are very important. In a recent study of applicants to the officers' training program in the Swedish Army, I had a chance to study this question, using the UPP test and its SD scales. (Previous studies had given similar results). Data were available for 5 groups:

A. Norm

B. Incumbents

C. Applicants (low consequences of test results)

D. Applicants (moderate consequences)

E. Applicants (high-stakes testing)

I expected increasing SD scale values in the order A - E. I also expected test scales to have the same rank order, if they were sensitive to SD, such as emotional stability. Finally, I expected the group differences in emotional stability to vanish if the test data were corrected for faking using the two SD scales (and a multiple regression model). For the results, see Figs. 1 and 2 below, and Table 1. 

Fig. 1. Means of SD scales

Fig. 2. Means of emotional stability before and after SD correction

Tabell 1. Mean values of emotional stability (standardized scales), uncorrected and corrected data, effect size and one-way ANOVA of group differences.
Grupp	Before correction	Corrected for SD
A. Norm	-0.25	-0.05
B. Incumbents	0.05	0.07
C. Applicants (low consequences of test results)	0.43	0.28
D. Applicants (moderate consequences)	0.56	0.06
E. Applicants (high-stakes testing)	0.73	0.11
Effect size (eta2)	0.147	0.006
One-way ANOVA	F(4,1638) = 70.693, p < 0.0005	F(4,1828) = 2.763, p = 0.026

Note that the effect size decreased to about 5 %.

In other work on leader effectiveness, using 360 degrees feedback as criterion, I found that the validities of the test scales increased after correction for SD according to the same method (Sjöberg, Bergman, Lornudd, & Sandahl, 2011), see Fig. 3. 

Fig. 3. Validities of uncorrected and corrected persnality scales

In conclusion, a simple method for correction for faking has been found to successfully remove about 95 % of the variance due to SD in test responses, and such a method increased the validity of the test scores against an external criterion. 

It is often argued that SD scales really measure "personality", such as need for approval, and not a tendency to distort responses. However, the present results strongly refute this view. It is very plausible that different levels of consequences of testing should lead to different levels of motivation for impression management, but unlikely that they should result in different levels of some personality dimension such as need for approval.

References

Bangerter, A., Roulin, N., & König, C. J. (2012). Personnel selection as a signaling game. [doi:10.1037/a0026078]. Journal of Applied Psychology, 97, 719-738.

Crowne, D. P., & Marlowe, D. (1960). A new scale of social desirability independent of psychopathology. Journal of Consulting and Clinical Psychology, 24, 349-354.

Fan, J., Gao, D., Carroll, S. A., Lopez, F. J., Tian, T. S., & Meng, H. (2012). Testing the efficacy of a new procedure for reducing faking on personality tests within selection contexts. [doi:10.1037/a0026655]. Journal of Applied Psychology, 97, 866-880.

Sjöberg, L. (2010/2012). A third generation personality test (SSE/EFI Working Paper Series in Business Administration No. 2010:3). Stockholm: Stockholm School of Economics.

Sjöberg, L., Bergman, D., Lornudd, C., & Sandahl, C. (2011). Sambandet mellan ett personlighetstest och 360-graders bedömningar av chefer i hälso- och sjukvården. (Relationship between a personality test and 360 degrees judgments of health care managers). Stockholm: Karolinska Institute, Institutionen för lärande, informatik, management och etik (LIME).

Validity of integrity tests

Traditionally the view has been that integrity tests (actually honesty tests) have very high validity, based on an early meta-analysis (Ones, Viswesvaran, & Schmidt, 1993). Some skeptical comments have pointed out that many of the studies in this meta-analysis came directly from reports from test vendors. Yet the high validity of integrity tests it has become an established truth, and a basis for an entire industry producing integrity tests, based on Schmidt and Hunter (1998) who wrote that the g-factor + integrity is the best basis for prediction of work performance. This is probably wrong.

A current and updated meta-analysis clearly shows that validities of integrity tests are not higher than 0.2, perhaps as low as 0.1 (Van Iddekinge, Roth, Raymark, & Odle-Dusseau, 2012a, 2012b), even if they are corrected for measurement error in criteria and range restriction in the test. The earlier estimates were at level 0.4, i.e. higher than the standard personality test. It appears now that the skeptics have been right: the high validities come from test providers' own information, independent research does not confirm therm. A rather high value of validity can be obtained with self-ratings of counterproductive behavior at work, but this is not very interesting.

This is an example of how early meta-analysis can result in errors. Van Iddekinge et al. have published a very  ambitious project. The result is clear. Integrity test seems not to have significant practical value. And then we have not even discussed that such tests can easily be faked..

References

One, DS, Viswesvaran, C., & Schmidt, FL (1993). Comprehensive meta-analysis of integrity test validities: findings and implications for personnel selection and theories of job performance. Journal of Applied Psychology Monograph, 78, 679-703.

Schmidt, F. L. & Hunter, J. E. (1998). The validity and utility of selection methods in personnel psychology: Practical and theoretical implications of 85 years of research findings. Psychological Bulletin, 124, 262-274.

Van Iddekinge, CH, Roth, PL, Raymark, PH, & Odle-Dusseau, HN (2012a). The criterion-related validity of integrity tests: An updated meta-analysis. [Doi: 10.1037/a0021196]. Journal of Applied Psychology, 97 (3), 499-530.

Van Iddekinge, CH, Roth, PL, Raymark, PH, & Odle-Dusseau, HN (2012b). The critical role of the research question, inclusion criteria the, and transparency in meta-Analyses of integrity test research: A reply to Harris et al. (2012) and Ones, Viswesvaran, and Schmidt (2012). [Doi: 10.1037/a0026551]. Journal of Applied Psychology, 97 (3), 543-549.

Optimal combination of personality and intelligence

Personality and intelligence are both related to job performance, but how should they be weighted for optimal results? The most straightforward approach is a linear combination, and indeed there is little evidence for other types of models. Once this is decided the final question is what weights should be given to the two types of information, in order to maximize predictive efficiency. It is well-known that they tend to be uncorrelated, hence the crucial question is how valid they are in relation to job performance criteria. Intelligence, or GMA (the g factor) correlates around 0.6 with job performance (Schmidt & Hunter, 1998). "Personality" is a less stringent term, and could mean many things. However, I shall take personality as referring to an optimal index of subscales, and such indices have been found to correlate around 0.55 with job performance (de Colli, 2011; Sjöberg, 2010; Sjöberg, Bergman, Lornudd, & Sandahl, 2011), after correction for measurement errors in criteria and range restriction in the independent variable (Schmidt, Shaffer, & Oh, 2008). Hence, intelligence and personality, in this sense, are equally efficient as predictors and an evidence-based strategy is to treat them that way, with equal weights.

It should be noted that the usual Big Five dimensions are much weaker predictors of job performance, as shown in a number of meta-analyses (Barrick, Mount, & Judge, 2001). To get an efficient personality predictor it is necessary to form an index based on focused and narrow scales (Bergner, Neubauer, & Kreuzthaler, 2010; Christiansen & Robie, 2011; Sjöberg, 2010/2012). Big Five personality tests are not sufficient for optimal prediction of job performance.

References

Barrick, M. R., Mount, M. K., & Judge, T. A. (2001). Personality and performance at the beginning of the new millennium: What do we know and where do we go next? International Journal of Selection and Assessment, 9, 9-30.

Bergner, S., Neubauer, A. C., & Kreuzthaler, A. (2010). Broad and narrow personality traits for predicting managerial success. [doi:10.1080/13594320902819728]. European Journal of Work and Organizational Psychology, 19, 177-199.

Christiansen, N. D., & Robie, C. (2011). Further consideration of the use of narrow trait scales. [doi:10.1037/a0023069]. Canadian Journal of Behavioural Science/Revue canadienne des sciences du comportement, 43, 183-194.

de Colli, D. (2011). Ett nytt svenskt arbetspsykologiskt test och arbetsprestation inom polisen – samtidig validitet: Mälardalens högskola, Akademin för hållbar samhälls- och teknikutveckling.

Schmidt, F. L., & Hunter, J. E. (1998). The validity and utility of selection methods in personnel psychology: Practical and theoretical implications of 85 years of research findings. Psychological Bulletin, 124, 262-274.

Schmidt, F. L., Shaffer, J. A., & Oh, I.-S. (2008). Increased accuracy for range restriction corrections: Implications for the role of personality and general mental ability in job and training performance. Personnel Psychology, 61, 827-868.

Sjöberg, L. (2010). Upp-testet och kundservice: Kriteriestudie. Forskningsrapport 2010:6. Stockholm: Psykologisk Metod AB.

Sjöberg, L. (2010/2012). A third generation personality test (SSE/EFI Working Paper Series in Business Administration No. 2010:3). Stockholm: Stockholm School of Economics.

Sjöberg, L., Bergman, D., Lornudd, C., & Sandahl, C. (2011). Sambandet mellan ett personlighetstest och 360-graders bedömningar av chefer i hälso- och sjukvården. Stockholm: Karolinska Institutet, Institutionen för lärande, informatik, management och etik (LIME).

Job interest and performance: a revised view

Is job interest of any importance to job performance? It seems very likely that it should be, but as pointed out by Nye et al. (Nye, Su, Rounds, & Drasgow, 2012), "interest measures are generally ignored in the employee selection literature" (p. 384). Part of the reason seems to be that previous meta-analytic work reported a very low correlation between interest and performance, only about 0.1 (Hunter & Hunter, 1984). However, Nye at al. criticized the often cited meta-analysis published by Hunter and Hunter and conducted a very extensive new analysis of the relation between interest and performance. They came up with a different conclusion: for studies where the interest scales matched the character of the jobs, the estimated correlation was 0.36, after correction for measurement errors and indirect range restriction. They concluded that interest should be considered in selection contexts. 

This is not the only example showing that earlier meta analyses of the effectiveness of predictors of job performance may be quite misleading. A recent publication on integrity tests by van Iddekinge et al. (2012) showed that earlier meta analytic work (Ones et al., 1993), cited by Hunter and Hunter, grossly over-estimated the validity of integrity tests.

The recent Nye at al. work  is undoubtedly very important. However, even stronger results can probably be obtained with specific interest measures. Vocational interest does not measure interest in a specific job, but in a class of jobs. In the UPP test, we measure routinely interest in the specific job under consideration, either in selection or in various types of follow-up. As an example, data from a study of employees in customer service in a finance company (Sjöberg, 2010) was re-analyzed. The correlation between job (not vocational) interest and supervisor rated performance on core job tasks was 0.55, after correction for measurement error and indirect range restriction. The specific interest measure is proximal to job performance, while vocational interest is distal, hence it should be expected to have a lower correlation.

What creates interest (Sjöberg, 2006)? For a given task content, optimal challenge may be the answer to the question. Interests are also probably somewhat elastic, i.e. you may develop a new interest under favorable circumstances (support, optimal challenge). Maybe one should try measure not only interest but also potential for developing interest. In a selection situation, it must be expected that interest scores are contaminated with impression management, and there is a need to correct for that factor. Alternatively, indirect measurement can be attempted, such as knowledge of facts. People who are strongly interested inform themselves about a job or area of study, hence know more. I tried this idea in the selection of applicants to the Stockholm School of Economics, with some success.

References

Hunter, J. E., & Hunter, R. F. (1984). Validity and utility of alternative predictors of job performance. Psychological Bulletin, 96, 72-98.

Nye, C. D., Su, R., Rounds, J., & Drasgow, F. (2012). Vocational interests and performance: A quantitative summary of over 60 years of research. Perspectives on Psychological Science, 7(4), 384-403.
Ones, D. S., Viswesvaran, C., & Schmidt, F. L. (1993). Comprehensive meta-analysis of integrity test validities: findings and implications for personnel selection and theories of job performance. Journal of Applied Psychology Monograph, 78, 679-703.
Van Iddekinge, C. H., Roth, P. L., Raymark, P. H., & Odle-Dusseau, H. N. (2012). The criterion-related validity of integrity tests: An updated meta-analysis. [doi:10.1037/a0021196]. Journal of Applied Psychology, 97(3), 499-530.

Sjöberg, L. (2006). What makes something interesting? (Review of the book, Exploring the psychology of interest by Paul J. Silvia). PsycCRITIQUES, 51 (46, Article 4), No Pagination Specified.

Sjöberg, L. (2010). UPP-testet och kundservice: Kriteriestudie. (The UPP test and customer service: A criterion study). Forskningsrapport 2010:6. Stockholm: Psykologisk Metod AB.
Sjöberg, L. (2010/2012). A third generation personality test (SSE/EFI Working Paper Series in Business Administration No. 2010:3). Stockholm: Stockholm School of Economics.
Click here,

Dealing with test complexity

People have a limited ability to make complex judgments without the support of computers and explicit decision rules. This fact has been well-known for many years. An often cited classic is a paper by Miller [12] . Expert judgments of many kinds, including the assessment of job applicants, have confirmed this general principle   [3; 8] . There are some interesting exceptions in special cases, if the experts get fast and clear feedback based on valid theory [9] .  These conditions are rarely present in the assessment of job applicants.

It is usual for judges to come to different conclusions if the information they use is complex and extensive - a common situation. Furthermore, assessments tend to vary over time. At the same time that we have these limitations in our judgment capacity, we have a tendency to fall prey to an illusion. The more information we get, the more confident we are - but beyond a modest limit, judgments become worse as in formation increases. See Fig. 1. 

Figure 1.  Decision quality as a function of amount of information. 

Most personality tests give a complicated picture of a person. This is reasonable since everyone "knows" that people are complicated. Popular tests provide results for 30-40 dimensions. It is likely that such abundance of information is popular due to the information illusion discussed above.  More information makes us more confident. Research has, however, shown that explicit rules for combining formation gives better results. Such a rule can simply be based on the decision maker's own systematic strategy, so-called boot-strapping [7] , or explicitly judged importance weights. The use of weights is an effective way of answering the question: "How do I interpret this test result?" The alterative approach is use a holistic evaluation based on the pattern of results. Holism has traditionally had a strong position in the interpretation of test results, but it cannot be justified on empirical and scientific grounds [14] . 

Subjective interpretation typically results in narrative texts which may be very credible, due to a number of psychological factors. Such factors have been discussed as enabling "cold reading", i.e. credible inferences about a person, which lack factual basis [13] . Historical examples show how credibility of the Rorschach test was established  by "wizards" who could seemingly produce surprisingly correct statements about a person on the basis of responses to  that test [18] , in spite of the fact that this test, as well as other projective techniques have been found to lack validity [6; 10] . I give two examples of research, which illustrate how illusory credibility may be established.
The Forer effect. Flattering texts, which are full of statements which are generally true  and which say "both A and its Opposite B" are perceived  as very accurate. Forer showed this in a classic study a long time ago [5] ; results which have been replicated many times [4; 16] .  

Forer gave a group of students a "test" which he said would reveal their personalities. After some time a returned with narrative texts said to be based on the responses to the test. Each students got his or her text, but they were all the same. They were asked to judge how well the texts described their personalities. About 90 % said that the texts fitted very well. Here is what they got (typical astronomical texts):

"You have a need for other people to like and admire you, and yet you tend to be critical of yourself. While you have some personality weaknesses you are generally able to compensate for them. You have considerable unused capacity that you have not turned to your advantage. Disciplined and self-controlled on the outside, you tend to be worrisome and insecure on the inside. At times you have serious doubts as to whether you have made the right decision or done the right thing. You prefer a certain amount of change and variety and become dissatisfied when hemmed in by restrictions and limitations. You also pride yourself as an independent thinker; and do not accept others' statements without satisfactory proof. But you have found it unwise to be too frank in revealing yourself to others. At times you are extroverted, affable, and sociable, while at other times you are introverted, wary, and reserved. Some of your aspirations tend to be rather unrealistic. "

MBTI and PPA excel in using statements of this type , and they provide popular reading for those who have taken the tests. They are perceived to be almost perfectly accurate and to give self insights, but they simply flatter [15]  and/or confirm already existing self beliefs. Once credibility is established the tester can give important advice about selection, team composition and personal development. No research exists, which shows such advice to be useful, but since the test report is so persuasive the advice is probably also believed.

The "Draw-a-man"-effect". The draw-a-man test is credible to many users although it has no demonstrated validity [17] . This is because of common-sense thinking about what various aspect of a drawing could mean. Example: large muscles mean problem with male self-image, large eyes imply paranoid tendencies, etc. Inn addition, there is selective memory of cases which supported these speculations, the others are forgotten or explained away [1; 2] .

The UPP test deals with complexity with aggregate variables, which are linear composites of selected subscales. Extensive research, over a period of 50 years,  has shown that this approach is superior to subjective integration of information [8; 11] . For a reveiew of work on UPP, click here.

References

[1]. Chapman, L. J., & Chapman, J. P. (1967). Genesis of popular but erroneous psychodiagnostic observations. Journal of Abormal Psychology, 73, 193-204.

[2]. Chapman, L. J., & Chapman, J. P. (1969). Illusory correlation as an obstacle to the use of valid psychodiagnostic signs. Journal of Abnormal Psychology, 74, 271-280.

[3]. Dawes, R. M., Faust, D., & Meehl, P. E. (1989). Clinical versus actuarial judgment. Science, 243, 1668-1674.

[4]. Dickson, D. H., & Kelly, I. W. (1985). The 'Barnum Effect in Personality Assessment: A Review of the Literature. Psychological Reports 57, 367-382.

[5]. Forer, B. R. (1949). The fallacy of personal validation: a classroom demonstration of gullibility. Journal of Abnormal & Social Psychology, 44, 118-123.

[6]. Garb, H. N., Lilienfeld, S. O., & Wood, J. M. (2004). Projective techniques and behavioral assessment. In S. N. Haynes & E. M. Heiby (Eds.), Comprehensive handbook of psychological assessment, Vol. 3: Behavioral assessment (pp. 453-469). Hoboken, NJ, US: John Wiley & Sons Inc.

[7]. Goldberg, L. R. (1970). Man versus model of man: A rationale plus some evidence for a method of improving clinical inferences. Psychological Bulletin, 73, 422-432.

[8]. Grove, W. M., & Meehl, P. E. (1996). Comparative efficiency of informal (subjective, impressionistic) and formal (mechanical, algorithmic) prediction procedures: The clinical-statistical controversy. Psychology, Public Policy, and Law, 2, 293-323.

[9]. Kahneman, D., & Klein, G. (2009). Conditions for intuitive expertise: A failure to disagree. [doi:10.1037/a0016755]. American Psychologist, 64, 515-526.

[10]. Lilienfeld, S. O., Wood, J. M., & Garb, H. N. (2000). The scientific status of projective techniques. Psychological Science in the Public Interest, 1, 27-66.

[11]. Meehl, P. E. (1954). Clinical versus statistical prediction: A theoretical analysis and a review of the evidence. Minneapolis: University of Minnesota Press.

[12]. Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63, 81-97.

[13]. Rowland, I. (2005). The full facts book of cold reading, 4th edition. London: Full Facts Books.

[14]. Ruscio, J. (2002). The emptiness of holism. Skeptical Inquirer, 26, 46-50.

[15]. Thiriart, P. (1991). Acceptance of personality test results. Skeptical Inquirer, 15, 166-172.

[16]. Trankell, A. (1961). Magi och förnuft i människobedömning. Stockholm: Bonnier.

[17]. Willcock, E., Imuta, K., & Hayne, H. (2011). Children’s human figure drawings do not measure intellectual ability. [doi:10.1016/j.jecp.2011.04.013]. Journal of Experimental Child Psychology, 110, 444-452.

[18]. Wood, J. M., Nezworski, M. T., Lilienfeld, S. O., & Garb, H. N. (2003). What's wrong with the Rorschach?: Science confronts the controversial inkblot test. San Francisco, CA, US: Jossey-Bass.

Publiceras flera "signifikanta" resultat än vad forskarna faktiskt funnit?

Det är en vanlig misstanke att ej signifikanta resultat inte publiceras och att därför den vetenskapliga litteraturen ger en felaktig bild av hur starka sambanden faktiskt är ("the file drawer problem"). En sådan felfaktor skulle snedvrida meta-analyser som normalt enbart bygger på publicerade arbeten. I en aktuell artikel har emellertid  Dalton et al. (2012) gått igenom dels ett stort antal publicerade arbeten, dels många opublicerade doktorsavhandlingar. Resultaten är slående: Det är ungefär lika många signifikanta samband i båda fallen. På grundval av denna omfattande studie kan man dra den slutsatsen att problemet med "the file drawer" inte existerar eller åtminstone att det är betydligt mindre allvarligt än vad man hittills trott.

Referens

Dalton, D. R., Agunis, H., Dalton, C. M., Bosco, F. A., & Pierce, C. A. (2012). Revisiting the file drawer problem in meta-analysis: Assessment  of published and nonpublished correlation matrices. Personnel Psychology, 65(2), 221-249.

Integritetstestens validitet

Traditionellt har det ansetts att integritetstest (egentligen test på ärlighet) har mycket hög validitet, på grundval av en tidig meta-analys (Ones, Viswesvaran, & Schmidt, 1993). En del skeptiska kommentarer har pekat på att en stor del av de studier denna analys byggde på ej var publicerade utan kom direkt från rapporter från testleverantörerna. Ändå har det blivit en etablerad sanning, och en grundval för en hel industri som producerar integritetstestningar, utifrån Schmidt och Hunter (1998) som skrev att g-faktorn + integritet är den bästa grunden för prognos av arbetsresultat. Det är nog fel.

En aktuell och uppdaterad meta-analys visar tydligt att validiteterna hos integritetstesten inte är högre än 0.2, kanske så låga som 0.1 (Van Iddekinge, Roth, Raymark, & Odle-Dusseau, 2012a, 2012b), t o m om de är korrigerade för mätfel i kriterierna och begränsad spridning i testen. De tidigare uppskattningarna låg på nivån 0.4, alltså högre än de vanliga personlighetstesten. Det tycks som om skeptikerna har haft rätt: de höga validiteterna kommer från testleverantörernas egen information, oberoende forskning bekräftar den inte. Ett ganska högt värde på validiteten kan man få mot självskattningar av kontraproduktivt beteende i jobbet, men detta är ganska ointressant. Skattningar av andra som kriterium ger validiteter om kring 0.1. Schmidt och Hunter uppskattade validiteten till 0.41, vilket nu framstår som starkt vilseledande.

Detta är ett exempel på att tidiga meta-analyser kan leda fel. Van Iddekinge et al. har gjort ett enormt ambitiöst arbete. Resultatet är tydligt. Integritetstest tycks inte ha nämnvärt praktiskt värde. Och då har vi inte ens diskuterat att sådana test, liksom alla, kan fejkas.

Referenser

Ones, D. S., Viswesvaran, C., & Schmidt, F. L. (1993). Comprehensive meta-analysis of integrity test validities: findings and implications for personnel selection and theories of job performance. Journal of Applied Psychology Monograph, 78, 679-703.
Schmidt, F. L., & Hunter, J. E. (1998). The validity and utility of selection methods in personnel psychology: Practical and theoretical implications of 85 years of research findings. Psychological Bulletin, 124, 262-274.

Van Iddekinge, C. H., Roth, P. L., Raymark, P. H., & Odle-Dusseau, H. N. (2012a). The criterion-related validity of integrity tests: An updated meta-analysis. [doi:10.1037/a0021196]. Journal of Applied Psychology, 97(3), 499-530.

Van Iddekinge, C. H., Roth, P. L., Raymark, P. H., & Odle-Dusseau, H. N. (2012b). The critical role of the research question, inclusion criteria, and transparency in meta-analyses of integrity test research: A reply to Harris et al. (2012) and Ones, Viswesvaran, and Schmidt (2012). [doi:10.1037/a0026551]. Journal of Applied Psychology, 97(3), 543-549.