ON SOME METHODOLOGICAL ASPECTS OF THE STUDY OF HUMAN INDIVIDUALITY
Abstract
Human individuality, presented on different levels (from biological to social ones), is of a high interest in Russian psychology, and the method of correlation design is widely used among researches, because it allows revealing relationships between multi-level properties of individuality. The present article examines several methodical aspects of the correlation analysis implementation, discussing problems and possible solutions. In particular, it considers the issue of nonlinear dependencies (parabolic, hyperbolic etc.), which are impossible to reveal by common correlation methods, but which can be uncovered by using nonlinear correlations, such as correlation index, correlation ratio, maximal information coefficient, distance correlation, maximal correlation, “partial moments” method. Furthermore, it considers the necessity of visualizing variables correlation (scatterplots) that enables to reveal hidden data structures, for example, subgroups. Special attention is paid to correlations corrections for restriction of range and related difficulties that are well-known, but scarcely researched in Russian psychology. In process of investigating plentiful pairwise correlations between individuality properties on different levels it is important to consider anissue of multiple comparisons, which, however, is rarely taken into the account by researches, leading to false results in many occasions. Moreover, the article examines robust statistical methods, particularly permutation tests and bootstrap. These methods combine robustness and high power. Finally, the study observes such issues as the completeness of results presentation and current debates about significance level, effect size and confidence intervals, reproducibility of psychological researches, and meta-analysis approach. Significance level has often been criticized; interval estimates and effect size were supposed to replace it. However, the problem of Null Hypothesis Significance Testing (NHST) has not been completely solved yet. A possible solution is presentation of complete data on research results including precise significance level, confidence intervals, effect size and etc. These estimations can be then applied in meta-analysis, which allows moving on to a new level of scientific generalizations.Downloads
Download data is not yet available.
References
1. Anan'ev B.G. Chelovek kak predmet poznaniya [Man as the Object of Knowledge].
St. Petersburg, “Piter” Publ., 2001. 288 p.
2. Grzhibovskiy A.M. [Correlation Analysis of Data Using Statistica and SPSS Software]. Nauka i Zdravoohranenie [Science and Healthcare], 2017, no. 1, pp. 7–36. (in Russ.).
3. Kabacoff R.I. R v deystvii. Analiz i vizualizaciya dannyh v programme R [R in Action. Data Analysis and Graphics with R]. Moscow, DMK Press Publ., 2016. 588 p.
4. Kalugin A.Yu. [The Use of Neural Networks in Psychological Research]. Iskusstvennyy intellekt v reshenii aktual'nyh social'nyh i ehkonomicheskih problem XXI veka [Artificial Intelligence in Solving Actual Social and Economic Problems of the XXI Century]. Perm', Perm State University Publ., 2018a, pp. 144–148. (in Russ.).
5. Kalugin A.Yu. [History and Prospects of Studying Integral Individuality within the System Approach]. Vestnik Permskogo universiteta. Filosofiya. Psikhologiya. Sotsiologiya [Perm University Herald. Series “Philosophy. Psychology. Sociology”]. 2018b, iss. 2, pp. 252–263. DOI: 10.17072/20787898/2018-2-252-263. (in Russ.).
6. Kalugin A.Yu. Cennostnaya napravlennost' lichnosti kak vyrazhenie smysloobrazuyushchey aktivnosti: struktura, dinamika i funkcii v strukture integral'noy individual'nosti (na materiale studenchestva): diss… kand.psikhol. nauk. [Value Orientation of the Personality as an Expression of MeaningMaking Activity: Structure, Dynamics and Function in the Structure of Integral Individuality (Based on the Study of Students). Cand. diss. (Psychology)]. Perm', 2015. 179 p.
7. Korneev A.A., Rasskazova E.I., Krichevets A.N., Koyfman A.Ya. [Criticism of Null Hypothesis Significance Testing: Limitations and Possible Ways Out. Part I]. Psihologicheskie issledovaniya [Psychological Studies]. 2016, vol. 9(45), p. 1. Available at: http://psystudy.ru/
index.php/num/2016v9n45/1231-korneev45.html. (accessed 2.09.2018). (in Russ.)
8. Kornilov S.A., Kornilova T.V. [Meta-Analytic Studies in Psychology]. Psihologicheskiy zhurnal [Psylogical Journal]. 2010, vol. 31(6), pp. 5–17. (in Russ.).
9. Kornilova T.V. [Main Trends in the Development of Methods of Psychological Research]. Ehksperimental'naya psihologiya v Rossii: tradicii i perspektivy [Experimental Psychology in Russia: Traditions and Perspectives]. Moscow, Institut psikhologii RAN Publ., 2010, pp. 42–46. (in Russ.).
10. Melas V.B., Salnikov D.I., Gudulina A.O. [The Numerical Compearing of Classical and Permutation Methods of Statistical Hypothesis Testing]. Vestnik Sankt-Peterburgskogo universiteta. Seriya 1. Matematika. Mekhanika. Astronomiya [Vestnik of Saint Petersburg University. Series 1. Mathematics. Mechanics. Astronomy]. 2016, vol. 3(61), pp. 415–423. DOI: 10.21638/11701/spbu01.2016.309. (in Russ.)
11. Merlin V.S. Ocherk teorii integral’nogo issledovaniya individual’nosti [Outline of the Theory of Individuality Integral Research]. Moscow, “Pedagogika” Publ., 1986. 256 p.
12. Nasledov A.D. Matematicheskie metody psihologicheskogo issledovaniya. Analiz i interpretaciya dannyh [Mathematical Methods of Psychological Research. Data Analysis and Interpretation].
St. Petersburg, “Rech'” Publ., 2008. 392 p.
13. Rusalov V.M. Temperament v strukture individual'nosti cheloveka: Differentsial'nopsikhofiziologicheskie i psikhologicheskie issledovaniya [Temperament in the Structure of Human Individuality: Psychophysiological Studies]. Moscow, Institut psikhologii RAN Publ., 2012. 528 p.
14. Sivuha S.V., Kozyak A.A. [On the Reform of Statistical Inference in Psychology]. Psihologiya. ZHurnal Vysshey shkoly ehkonomiki [Psychology. Journal of the Higher School of Economics]. 2009, vol. 6(4), pp. 66–86. (in Russ.).
15. Ferster Eh., Renc B. Metody korrelyacionnogo i regressionnogo analiza [Methods of Correlation and Regression Analysis]. Moscow, Finansy i statistika Publ., 1983. 304 p.
16. Shitikov V.K., Rozenberg G.S. Randomizaciya i butstrep: statisticheskiy analiz v biologii i ehkologii s ispol'zovaniem R [Randomization and Bootstrap: Statistical Analysis in Biology and Ecology Using R]. Tol'yatti, “Kassandra” Publ., 2013. 314 p.
17. Breiman L., Friedman J.H. Estimating Optimal Transformations for Multiple Regression and Correlation. Journal of the American Statistical Association. 1985, vol. 80(391), pp. 580–598. DOI:
10.1080/01621459.1985.10478157.
18. Bretz F., Hothorn T., Westfall P. Multiple Comparisons Using R. Boca Raton, Chapman & Hall/CRC Press, 2010. 205 p.
19. Cohen J. The Earth is Round (p < .05). American Psychologist. 1994, vol. 49(12), pp. 997– 1003. DOI: 10.1037/0003-066X.49.12.997.
20. Cumming G. Understanding the New Statistics: Effect Sizes, Confidence Intervals, and MetaAnalysis. New York, Routledge Publ., 2012. 519 p. DOI: 10.4324/9780203807002.
21. Cumming G. The New Statistics: Why and How. Psychological Science. 2014, vol. 25(1), pp. 7–29. DOI: 10.1177/0956797613504966.
22. Deebani W., Kachouie N.N. Ensemble Correlation Coefficient. ISAIM, 2018. Available at: http://isaim2018.cs.virginia.edu/papers/ISAIM2018_Deebani_Kachouie.pdf. (accessed 25.09.2018).
23. Hunter J.E., Schmidt F.L. Methods of Meta-Analysis: Correcting Error and Bias in Research Findings. 2nd ed. Thousand Oaks, Sage Publications, 2004. 582 p.
24. Kline R.B. Beyond Significance Testing: Statistics Reform in the Behavioral Sciences. Washington, American Psychological Association Publ., 2013. 350 p. DOI: 10.1037/14136-000.
25. McAdams D.P., Pals J.L. A New Big Five: Fundamental Principles for an Integrative Science of Personality. American Psychologist. 2006, vol. 61(3), pp. 204–217. DOI: 10.1037/0003066X.61.3.204.
26. McCrae R.R., Costa Jr.P.T. The Five-Factor Theory of Personality. Handbook of Personality: Theory and Research. 3rd ed. New York, NY, USA, Guilford Press, 2008, pp. 159–181.
27. Open Science Collaboration. Estimating the Reproducibility of Psychological Science. Science. 2015, vol. 349(6251), pp. 943. DOI: 10.1126/science.aac4716.
28. Publication Manual of the American Psychological Association. 6th ed. Washington, DC, American Psychological Association Publ., 2010. 272 p.
29. Reshef D.N., Reshef Y.A., Finucane H.K., Grossman S.R., McVean G., Turnbaugh P.J., Lander E.S., Mitzenmacher M., Sabeti, P.C. Detecting Novel Associations in Large Data Sets. Science.
2011, vol. 334(6062), pp. 1518–1524. DOI: 10.1126/science.1205438
30. Revelle W. An Introduction to Psychometric Theory with Applications in R. Available at:
http://www.personality-project.org/r/book/chapter4.pdf. (accessed 26.07.2018).
31. Szekely G.J., Rizzo M.L., Bakirov N.K. Measuring and Testing Dependence by Correlation of
Distances. The Annals of Statistics. 2007, vol. 35(6), pp. 2769–2794. DOI: 10.1214/009053607000000505.
32. Tellez A., Garcia C.H., Corral-Verdugo V. Effect Size, Confidence Intervals and Statistical Power in Psychological Research. Psychology in Russia: State of the Art. 2015, vol. 8(3), pp. 27–46. DOI: 10.11621/pir.2015.0303.
33. Tran D.M. Robustness of Two Formulas to Correct Pearson Correlation for Restriction of Range: Dissertation. Atlanta, Georgia State University Publ., 2011. Available at: http://scholarworks.gsu.edu/eps_diss/84. (accessed 15.06.2018).
34. Viole F., Nawrocki D.N. Deriving Nonlinear Correlation Coefficients from Partial Moments. SSRN Electronic Journal (September 18, 2012). DOI: 10.2139/ssrn.2148522.
St. Petersburg, “Piter” Publ., 2001. 288 p.
2. Grzhibovskiy A.M. [Correlation Analysis of Data Using Statistica and SPSS Software]. Nauka i Zdravoohranenie [Science and Healthcare], 2017, no. 1, pp. 7–36. (in Russ.).
3. Kabacoff R.I. R v deystvii. Analiz i vizualizaciya dannyh v programme R [R in Action. Data Analysis and Graphics with R]. Moscow, DMK Press Publ., 2016. 588 p.
4. Kalugin A.Yu. [The Use of Neural Networks in Psychological Research]. Iskusstvennyy intellekt v reshenii aktual'nyh social'nyh i ehkonomicheskih problem XXI veka [Artificial Intelligence in Solving Actual Social and Economic Problems of the XXI Century]. Perm', Perm State University Publ., 2018a, pp. 144–148. (in Russ.).
5. Kalugin A.Yu. [History and Prospects of Studying Integral Individuality within the System Approach]. Vestnik Permskogo universiteta. Filosofiya. Psikhologiya. Sotsiologiya [Perm University Herald. Series “Philosophy. Psychology. Sociology”]. 2018b, iss. 2, pp. 252–263. DOI: 10.17072/20787898/2018-2-252-263. (in Russ.).
6. Kalugin A.Yu. Cennostnaya napravlennost' lichnosti kak vyrazhenie smysloobrazuyushchey aktivnosti: struktura, dinamika i funkcii v strukture integral'noy individual'nosti (na materiale studenchestva): diss… kand.psikhol. nauk. [Value Orientation of the Personality as an Expression of MeaningMaking Activity: Structure, Dynamics and Function in the Structure of Integral Individuality (Based on the Study of Students). Cand. diss. (Psychology)]. Perm', 2015. 179 p.
7. Korneev A.A., Rasskazova E.I., Krichevets A.N., Koyfman A.Ya. [Criticism of Null Hypothesis Significance Testing: Limitations and Possible Ways Out. Part I]. Psihologicheskie issledovaniya [Psychological Studies]. 2016, vol. 9(45), p. 1. Available at: http://psystudy.ru/
index.php/num/2016v9n45/1231-korneev45.html. (accessed 2.09.2018). (in Russ.)
8. Kornilov S.A., Kornilova T.V. [Meta-Analytic Studies in Psychology]. Psihologicheskiy zhurnal [Psylogical Journal]. 2010, vol. 31(6), pp. 5–17. (in Russ.).
9. Kornilova T.V. [Main Trends in the Development of Methods of Psychological Research]. Ehksperimental'naya psihologiya v Rossii: tradicii i perspektivy [Experimental Psychology in Russia: Traditions and Perspectives]. Moscow, Institut psikhologii RAN Publ., 2010, pp. 42–46. (in Russ.).
10. Melas V.B., Salnikov D.I., Gudulina A.O. [The Numerical Compearing of Classical and Permutation Methods of Statistical Hypothesis Testing]. Vestnik Sankt-Peterburgskogo universiteta. Seriya 1. Matematika. Mekhanika. Astronomiya [Vestnik of Saint Petersburg University. Series 1. Mathematics. Mechanics. Astronomy]. 2016, vol. 3(61), pp. 415–423. DOI: 10.21638/11701/spbu01.2016.309. (in Russ.)
11. Merlin V.S. Ocherk teorii integral’nogo issledovaniya individual’nosti [Outline of the Theory of Individuality Integral Research]. Moscow, “Pedagogika” Publ., 1986. 256 p.
12. Nasledov A.D. Matematicheskie metody psihologicheskogo issledovaniya. Analiz i interpretaciya dannyh [Mathematical Methods of Psychological Research. Data Analysis and Interpretation].
St. Petersburg, “Rech'” Publ., 2008. 392 p.
13. Rusalov V.M. Temperament v strukture individual'nosti cheloveka: Differentsial'nopsikhofiziologicheskie i psikhologicheskie issledovaniya [Temperament in the Structure of Human Individuality: Psychophysiological Studies]. Moscow, Institut psikhologii RAN Publ., 2012. 528 p.
14. Sivuha S.V., Kozyak A.A. [On the Reform of Statistical Inference in Psychology]. Psihologiya. ZHurnal Vysshey shkoly ehkonomiki [Psychology. Journal of the Higher School of Economics]. 2009, vol. 6(4), pp. 66–86. (in Russ.).
15. Ferster Eh., Renc B. Metody korrelyacionnogo i regressionnogo analiza [Methods of Correlation and Regression Analysis]. Moscow, Finansy i statistika Publ., 1983. 304 p.
16. Shitikov V.K., Rozenberg G.S. Randomizaciya i butstrep: statisticheskiy analiz v biologii i ehkologii s ispol'zovaniem R [Randomization and Bootstrap: Statistical Analysis in Biology and Ecology Using R]. Tol'yatti, “Kassandra” Publ., 2013. 314 p.
17. Breiman L., Friedman J.H. Estimating Optimal Transformations for Multiple Regression and Correlation. Journal of the American Statistical Association. 1985, vol. 80(391), pp. 580–598. DOI:
10.1080/01621459.1985.10478157.
18. Bretz F., Hothorn T., Westfall P. Multiple Comparisons Using R. Boca Raton, Chapman & Hall/CRC Press, 2010. 205 p.
19. Cohen J. The Earth is Round (p < .05). American Psychologist. 1994, vol. 49(12), pp. 997– 1003. DOI: 10.1037/0003-066X.49.12.997.
20. Cumming G. Understanding the New Statistics: Effect Sizes, Confidence Intervals, and MetaAnalysis. New York, Routledge Publ., 2012. 519 p. DOI: 10.4324/9780203807002.
21. Cumming G. The New Statistics: Why and How. Psychological Science. 2014, vol. 25(1), pp. 7–29. DOI: 10.1177/0956797613504966.
22. Deebani W., Kachouie N.N. Ensemble Correlation Coefficient. ISAIM, 2018. Available at: http://isaim2018.cs.virginia.edu/papers/ISAIM2018_Deebani_Kachouie.pdf. (accessed 25.09.2018).
23. Hunter J.E., Schmidt F.L. Methods of Meta-Analysis: Correcting Error and Bias in Research Findings. 2nd ed. Thousand Oaks, Sage Publications, 2004. 582 p.
24. Kline R.B. Beyond Significance Testing: Statistics Reform in the Behavioral Sciences. Washington, American Psychological Association Publ., 2013. 350 p. DOI: 10.1037/14136-000.
25. McAdams D.P., Pals J.L. A New Big Five: Fundamental Principles for an Integrative Science of Personality. American Psychologist. 2006, vol. 61(3), pp. 204–217. DOI: 10.1037/0003066X.61.3.204.
26. McCrae R.R., Costa Jr.P.T. The Five-Factor Theory of Personality. Handbook of Personality: Theory and Research. 3rd ed. New York, NY, USA, Guilford Press, 2008, pp. 159–181.
27. Open Science Collaboration. Estimating the Reproducibility of Psychological Science. Science. 2015, vol. 349(6251), pp. 943. DOI: 10.1126/science.aac4716.
28. Publication Manual of the American Psychological Association. 6th ed. Washington, DC, American Psychological Association Publ., 2010. 272 p.
29. Reshef D.N., Reshef Y.A., Finucane H.K., Grossman S.R., McVean G., Turnbaugh P.J., Lander E.S., Mitzenmacher M., Sabeti, P.C. Detecting Novel Associations in Large Data Sets. Science.
2011, vol. 334(6062), pp. 1518–1524. DOI: 10.1126/science.1205438
30. Revelle W. An Introduction to Psychometric Theory with Applications in R. Available at:
http://www.personality-project.org/r/book/chapter4.pdf. (accessed 26.07.2018).
31. Szekely G.J., Rizzo M.L., Bakirov N.K. Measuring and Testing Dependence by Correlation of
Distances. The Annals of Statistics. 2007, vol. 35(6), pp. 2769–2794. DOI: 10.1214/009053607000000505.
32. Tellez A., Garcia C.H., Corral-Verdugo V. Effect Size, Confidence Intervals and Statistical Power in Psychological Research. Psychology in Russia: State of the Art. 2015, vol. 8(3), pp. 27–46. DOI: 10.11621/pir.2015.0303.
33. Tran D.M. Robustness of Two Formulas to Correct Pearson Correlation for Restriction of Range: Dissertation. Atlanta, Georgia State University Publ., 2011. Available at: http://scholarworks.gsu.edu/eps_diss/84. (accessed 15.06.2018).
34. Viole F., Nawrocki D.N. Deriving Nonlinear Correlation Coefficients from Partial Moments. SSRN Electronic Journal (September 18, 2012). DOI: 10.2139/ssrn.2148522.
References on translit
Published
2019-07-15
How to Cite
Kalugin, A. (2019). ON SOME METHODOLOGICAL ASPECTS OF THE STUDY OF HUMAN INDIVIDUALITY. Psychology. Psychophysiology, 12(2), 29-40. https://doi.org/10.14529/jpps190203
Issue
Section
Psychodiagnostics
Copyright (c) 2019 Psychology. Psychophysiology
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
