Medical Radiology and Radiation Safety. 2019. Vol. 64. No. 6. P. 12–24

DOI: 10.12737/1024-6177-2019-64-6-12-24

A.N. Koterov1, L.N. Ushenkova1, E.S. Zubenkova1, M.V. Kalinina1, A.P. Biryukov1, E.M. Lastochkina1, D.V. Molodtsova1, А.А. Wainson2

Strength of Association.
Report 2. Graduations of Correlation Size

1. A.I. Burnasyan Federal Medical Biophysical Center, Moscow, Russia. E-mail: Этот адрес электронной почты защищен от спам-ботов. У вас должен быть включен JavaScript для просмотра. ;
2. N.N. Blokhin National Medical Research Center of Oncology, Moscow, Russia

A.N. Koterov – Head of Lab., Dr. Sci. Biol.;
L.N. Ushenkova – Leading Researcher, PhD Biol.;
E.S. Zubenkova – Leading Researcher, PhD Biol.;
M.V. Kalinina – Engineer;
A.P. Biryukov – Head of Dep., Dr. Sci. Med., Prof.;
E.M. Lastochkina – Engineer;
D.V. Molodtsova – Engineer;
A.A. Wainson – Head of Group, Dr. Sci. Biol., Prof.


Purpose: To summarize data on graduation of the effect size on the base of Hill’s first causality criterion ‘strength of association’ on the magnitude of the correlation coefficient (mainly Pearson r).
Material and methods: Survey of published sources: monographs, handbooks, papers, educational material on statistics in various disciplines (including on-line), etc. (121 references; of which more than 20 textbooks on statistical methods and statistics in psychology and 8 textbooks on epidemiology).

Results: Estimation of the strength of association by the correlation size is most common in psycho-sociological disciplines and is almost never used in epidemiology (since the establishment of a fact of statistically significant association/correlation in epidemiology is only the initial stage of evidence, unlike the experimental and named disciplines). A number of known scales for r were obtained: the Chaddok scale (R.E. Chaddock) from 1925, which is now apparently not used abroad, but widely represented in the countries of the former USSR, the Cohen scale (J. Cohen) from 1969–1988, reflecting the ‘soft’ criteria of causality in psychology, D.E. Hinkle with co-authors scale (1979–2003) and the Evans scale (J.D. Evans) from 1996. A number of other graduations, published in the singular, are also given. A total of at least 16 different scales of varying degrees were collected for the correlation coefficient r (1925–2019). The information about the value of r for correlations, which should be neglected was presented. Depending on the source, this is r <0.1; r <0.2 or r <0.3. The data on the possibility of transferring graduations from the Pearson coefficient r to the Spearman correlation coefficient and other parameters of the effect size are given.
The question of the difference between estimation of strength of association in epidemiology and medicine and in psycho-sociological disciplines is considered. Unlike the second, in epidemiology and medicine a small value of the correlation coefficient does not necessarily mean a small effect size.

Conclusions: To estimate the value of r one should use the most common and officially established scales, with the exception of the strongly ‘soft’ Cohen scale. The present study can be used as a reference guide on the graduations of effect size on r for a wide variety of observation disciplines.

Key words: graduation of effect size, correlation coefficient, epidemiology, psychology


1. Causality in the Sciences. Ed. by P.M. Illari, Russo F, Williamson J. – New York: Oxford University Press, 2011. 882 p. DOI: 10.1093/acprof:oso/9780199574131.001.0001.
2. Doll R. Weak associations in epidemiology: importance, detection, and interpretation. J Epidemiol. 1996;6(4 Suppl):S11-20.
3. Handbook of Epidemiology. 2nd Ed. Ed. by W. Ahrens, I. Pigeot. – New York, Heidelberg, Dordrecht, London: Springer, 2014. 2498 p.
4. Kudryashov YuB. Radiation Biophysics (ionizing radiation). Ed. by V.C. Mazurik, M.F. Lomanov. – M.: FIZMATLIT, 2004. 448 p. (In Russian).
5. Yarmonenko SP, Wainson AA. Radiobiology of Humans and Animals. – Moscow, Visshaya Shkola, 2004. 549 p. (In Russian).
6. Radiation Medicine. Ed. by L.A. Il’yin. In four volumes. Volume 1. Theoretical Foundations of Radiation Medicine. – Moscow: Izd. AT, 2004. 992 p. (In Russian).
7. Il’yn LA, Korenkov IP, Narkevich BYa. Radiation Hygiene. A textbook. 5th Ed, revised and added. – M.: GEOTAR-Media, 2017. 416 p. (In Russian).
8. UNSCEAR 2006. Report to the General Assembly, with Scientific Annexes. Annex A. Epidemiological studies of radiation and cancer. United Nations. – New York, 2008. P. 17-322.
9. BEIR VII Report 2006. Phase 2. Health Risks from Exposure to Low Levels of Ionizing Radiation. Committee to Assess Health Risks from Exposure to Low Levels of Ionizing Radiation, – National Research Council. (Address data 2019.01.23).
10. ICRP Publication 103. The 2007 Recommendations of the International Commission on Radiological Protection. Annals of the ICRP. Ed. by J. Valentin. Amsterdam – New York: Elsevier, 2007. 329 p.
11. Hill BA. The environment and disease: association or causation? Proc Roy Soc Med. 1965;58(5):295-300. DOI: 10.1177/0141076814562718.
12. Glynn JR. A question of attribution. Lancet. 1993;342(8870):530-2.
13. National Research Council. Science and judgment in risk assessment. – Washington, DC: National Academy Press, 1994. 672 p. DOI: 10.17226/2125.
14. Merrill RM, Frankenfeld CL, Freeborne N, Mink M. Behavioral Epidemiology. Principles and Applications. – Burlington: Jones & Bartlett Learning, LLC, 2016. 298 p.
15. Forensic Epidemiology in the Global Context. Ed. by S. Loue. – New York: Springer, 2013. 157 p.
16. Strom BL. Study designs available for pharmacoepidemiology studies. In: Pharmacoepidemiology. 3rd Ed. Ed. by B.L. Strom. – Baffins Lane, Chichester, West Sussex: John Wiley & Sons Ltd, 2000. P. 17-30.
17. Susser M. What is a cause and how do we know one? A grammar for pragmatic epidemiology. Amer J Epidemiol. 1991;133(7):635-48. DOI: 10.1093/oxfordjournals.aje.a115939.
18. Evans AS. Causation and disease: The Henle-Koch postulates revisited. Yale J Biol Med. 1976;49(2);175-95.
19. Koterov AN. Causal criteria in medical and biological disciplines: history, essence and Radiation Aspect. Report 1. Problem statement, conception of causes and causation, false associations. Radiats Biol Radioecol. (‘Radiation biology. Radioecology’, Moscow). 2019;59(1):5-36. DOI: 10.1134/S0869803119010065. (In Russian. English abstract.)
20. Blackburn H, Labarthe D. Stories from the evolution of guidelines for causal inference in epidemiologic associations: 1953-1965. Amer J Epidemiol. 2012;176(12):1071-7. DOI: 10.1093/aje/kws374.
21. Schlesselman JJ. ‘Proof’ of cause and effect in epidemiologic studies: criteria for judgment. Prev Med. 1987;16(2):195-210. DOI: 10.1016/0091-7435(87)90083-1.
22. Bhopal RS. Concepts of Epidemiology: Integrated the ideas, theories, principles and methods of epidemiology. 3rd Ed. – Oxford: University Press, 2016. 442 p.
23. The Health Consequences of Smoking: A Report of the Surgeon General Rockville, MD: Office of the Surgeon General, US Public Health Service, 2004. 910 p. (Address data 2019.01.23).
24. Goodman SN, Samet JM. Cause and Cancer Epidemiology. In: Schottenfeld and Fraumeni Cancer Epidemiology and Prevention. 4th Ed. Ed. by M.J. Thun et al. – New York: Oxford University Press. Printed by Sheridan Books, Inc, USA, 2018. P. 97-104.
25. Vlasov VV. Epidemiology. 2nd Ed, rev. – Moscow: GEOTAR-Media, 2006. 464 p. (In Russian).
26. Answers. Statistics. Offset – Minsk: BSU, 2010. 38 p. (In Russian).
27. Pearson Correlation Criterion. Site Medical Statistics. (Address data 2019.01.23). (In Russian).
28. Cheat Sheet by statistics. Russia, 2013. 170 p. Site StudFiles. (Address data 2019.01.26). (In Russian).
29. Schwab JJ, Schwab ME. Sociocultural Roots of Mental Illness. An Epidemiologic Survey. – New York: Springer US, 1978. 338 p.
30. Kornysheva EA, Platonov DY, Rodionov AA, Shabashov AE. Epidemiology and Statistics as Tools of Evidence-Based Medicine. 2nd Ed, revised and updated. Tver, 2009. 80 p. (In Russian).
31. Koterov AN, Ushenkova LN, Zubenkova ES, et al. Strength of association. Report 1. Graduation of relative risk. Medical Radiology and Radiation Safety. 2019;64(4):5-15. DOI: 10.12737/article_5d1adb25725023.14868717 (In Russian. English abstract.)
32. Cohen J. Statistical power analysis for the behavioral sciences. 2nd ed. Hillsdale. – Mahwah, NJ: Lawrence Erlbaum Associates. 1988. 567 p.
33. Bushman BJ, Anderson CA. Media violence and the American public. Scientific facts versus media misinformation. Amer Psychol. 2001;56(6-7):477-89. DOI: 10.1037/0003-066X.56.6-7.477.
34. Ferguson CJ. Is psychology research really as good as medical research? Effect size comparisons between psychology and medicine. Rev Gen  Psychol. 2009;13(2):130-6. DOI: 10.1037/a0015103.
35. Ferguson CJ. Everybody knows psychology is not a real science: Public perceptions of psychology and how we can improve our relationship with policymakers, the scientific community, and the general public. Amer Psychologist. 2015;70(6):527-42. DOI: 10.1037/a0039405.
36. Epidemiology: Principles and Practical Guidelines. Ed. by J. Van den Broeck, J.R. Brestoff. – Dordrecht: Springer, 2013. 621 p.
37. Nesselroade KP, Grimm LG. Statistical Applications for the Behavioral and Social Sciences. 2nd Ed. – New York: John Wiley & Sons, 2019. 930 p.
38. Egilman D, Kim J, Biklen M. Proving causation: the use and abuse of medical and scientific evidence inside the courtroom – an epidemiologist’s critique of the judicial interpretation of the Daubert ruling. Food Drug Law J. 2003;58(2):223-50.
39. Hunter RJ, Jr, Shannon JH, Amoroso HJ. How to manage issues relating to the use of trial experts: standards for the introduction of expert testimony through judicial ‘Gate-Keeping’ and scientific verification. J Man  Strategy. 2018;9(1): 11 p. DOI: 10.5430/jms.v9n1p1.
40. Guzelian PS, Victoroff MS, Halmes NC, et al. Evidence-based toxicology: a comprehensive framework for causation. Hum Exp Toxicol. 2005;24(4):161-201. DOI: 10.1191/0960327105ht517oa.
41. Chaddock RE. Principles and methods of statistics. – Boston, New York, [etc.]. 1925. 471 p.
42. Bruce D, Reineke LH. Correlation alinement charts in forest research. A method of solving problems in curvilinear multiple correlation. USA Department of Agriculture, Washington. Technical Bulletin № 210. February 1931. 88 p.
43. Sturtevant AP. Quantitative demonstration of the presence of spores of Bacillus larvae in honey contaminated by contact with American foulbrood. J Agricult Res. 1936;52(9):697-704.
44. Trask PD. Relation of salinity to the calcium carbonate content of marine sediments. Professional paper 186–N. In: United States Geological Survey Professional Paper. Property of Michigan Libraies. Washington: USA Government Printing Office, 1936. P. 273-99. DOI: 10.3133/pp186N.
45. Correlation strength indicators. Site StudFiles. (Address data 2019.01.26). (In Russian).
46. Sobolev I, Babichenko S. Application of the wavelet transform for feature extraction in the analysis of hyperspectral laser-induced fluorescence data. Int  J Remote Sensing. 2013;34(20):7218-35. DOI: 10.1080/01431161.2013.817714.
47. Buriak A, Vasylieva T, Lyeonov S. Systemically important domestic banks: an indicator-based measurement approach for the Ukrainian banking system. Prague Economic Papers. 2015;24(6):715-28. DOI: 10.18267/j.pep.531.
48. Sapon N, Nikiforova A. Correlation between access to health care and stroke mortality. Ukrainian Neurosurg  J. 2016(2):54-62. (Address data: 02.02.2019).
49. Rouiga IR, Vladimirova ON, Belyakova GY, et al. Methodological aspects of the regional innovative development evaluation with focus on investment flows. Indian J Sci Technol. 2016;9(37): 9 p. DOI: 10.17485/ijst/2016/v9i37/102175.
50. Zhanatauov SU. The inverse model of multiple linear regression analysis. ISJ Theoretical & Applied Science. 2018;60(4):201-12. DOI: 10.15863/TAS.
51. Gubin AV, Prudnikova OG, Kamysheva VV, et al. Clinical testing of the Russian version of the SRS-22 questionnaire for adult scoliosis patients. Hirurgia Pozvonochnika (Spine surgery). 2017;14(2):31-40. DOI: 10.14531/ss2017.2.31-40. (In Russian).
52. Cohen J. The statistical power of abnormal-social psychological research: a review. J Abnorm Soc Psychol. 1962;65(3):145-53. DOI: 10.2307/1161884.
53. Cohen J. Power Primer. Psychological Bulletin. 1992;112(1):155-9. DOI: 10.1037/0033-2909.112.1.155.
54. Lomax RG, Hahs-Vaughn DL. Statistical Concepts. A Second Course. 4th Ed. – New-York: Taylor & Francis Group, LLC, 2012. 516 p.
55. Divaris K, Vann WF. Jr, Baker AD, Lee JY. Examining the accuracy of caregivers’ assessments of young children’s oral health status. J Amer Dent Assoc. 2012;143(11):1237-47. DOI: 10.14219/jada.archive.2012.0071.
56. Neill J. Survey research & design in psychology. Lecture 4. 2018. (Address data 2019.01.29).
57. Yavna DV, Kupriyanov IV, Bunyaeva MV. Sensory and perceptual processes: a tutorial. Under scientific. ed. V.V. Babenko. – Rostov-on-Don: Publishing House of the Southern Federal University, 2016. 140 p. (In Russian).
58. Cohen BH, Lea RB. Essentials of Statistics for the Social and Behavioral Sciences. – Hoboken, New Jersey: John Wiley & Sons, 2004. 291 p.
59. Bakeman R, Robinson B.F. Understanding Statistics in the Behavioral Sciences. – Lawrence Erlbaum Associates, 2005. 363 p.
60. Wilcox R. Modern Statistics for the Social and Behavioral Sciences. A Practical Introduction. – CRC Press. Taylor & Francis Group, 2012. 840 p.
61. Aron AC. Statistics for the Behavioral and Social Sciences: A Brief Course. 5th Ed. – Pearson Education Limited, 2014. 486 p.
62. Kraska-Miller M, Nonparametric Statistic for Social and Behavioral Sciences. – CRC Press. Taylor & Francis Group, 2014. 232 p.
63. Gravetter FJ, Wallnau LB. Statistics for the Behavioral Sciences. 10th Ed. – Mason, OH, United States: Cengage Learning, 2017. 755 p.
64. Meyer GJ, Finn SE, Eyde LD, et al. Psychological testing and psychological assessment. A review of evidence and issues. Amer Psychol. 2001;56(2):128-65. DOI: 10.1037/0003-066X.56.2.128.
65. Hemphill JF. Interpreting the magnitudes of correlation coefficients. Amer Psychol. 2003;58(1):78-9. DOI: 10.1037/0003-066X.58.1.78.
66. Elementary Statistics. Tutorials. Effect size. Site Emory University. (Address data 2019.01.29).
67. Rosenthal JA. Qualitative descriptors of strength of association and effect size. J Soc Serv Res. 1996;21(4):37-59. 10.1300/J079v21n04_02.
68. Berry KJ, Johnston JE, Mielke PW, Jr. The Measurement of Association. A Permutation Statistical Approach. – Cham: Springer Nature Switzerland AG, 2018.  647 p.
69. De Menezes RF, Bergmann A, Thuler LC. Alcohol consumption and risk of cancer: a systematic literature review. Asian Pac J Cancer Prev. 2013;14(9):4965-72.
70. Rosenthal R. Effect sizes in behavioral and biomedical research: estimation and interpretation. In: Validity and Social Experimentation: Donald Campbell’s Legacy. Ed. by L. Bickman. – Newbury Park, CA: Sage. 2000;1: P. 121-39.
71. Garb HN, Klein DF, Grove WM. Comparison of medical and psychological psychological tests. Amer Psychol. 2002;57(2):137-8. DOI: 10.1037/0003-066X.57.2.137.
72. Rosnow RL, Rosenthal R. Effect sizes for experimenting psychologists. Canadian J   Exper  Psychol. 2003;57(3):221-37. DOI: 10.1037/h0087427.
73. Rutledge T, Loh C. Effect sizes and statistical testing in the determination of clinical significance in behavioral medicine research. Ann Behav Med. 2004;27(2):138-45. DOI: 10.1207/s15324796abm2702_9.
74. Steering Committee of the Physicians Health Study Research. Group. Preliminary report: Findings from the aspirin component of the ongoing physicians’ health study. N Engl J Med. 1988;318(4):261-4. DOI: 10.1056/NEJM198801283180431.
75. Steering Committee of the Physicians’ Health Study Research Group. Final report on the aspirin component of the ongoing Physicians’ Health Study. N Engl J Med. 1989;321(3):129-35. DOI: 10.1056/NEJM198907203210301.
76. Wuensch K. Cohen’s conventions for small, medium, and large effects. East Carolina University. 2009. Site University of Cambridge. MRC. Cognition and Brain Science Unite. MRC CBU Wiki. (Address data 2019.01.18); DOC: (Address data 2019.01.18).
77. Murphy KR, Myors B. Statistical Power Analysis. A Simple and General Model for Traditional and Modern Hypothesis Tests. 2nd Ed. – New York: Lawrence Erlbaum Associates, 2004. 160 p.
78. Kline RB. Beyond Significance Testing. Statistics Reform in the Behavioral Sciences. 6th Ed. – Baltimore: United Book Press, 2013. 349 p.
79. UNSCEAR 2012. Report to the General Assembly, with Scientific Annexes. Annex A. Attributing health effects to ionizing radiation exposure and inferring risks. – New York. 2015. 86 p.
80. Tallacchini M. Before and beyond the precautionary principle: epistemology of uncertainty in science and law. Toxicol Appl Pharmacol. 2005;207(2 Suppl):645-51. DOI: 10.1016/j.taap.2004.12.029.
81. Stirling A, Coburn J. From CBA to precautionary appraisal: practical responses to intractable problems. Hastings Cent Rep. 2018;48(Suppl 1):S78-87. DOI: 10.1002/hast.823.
82. Francis T, Korns R, Voight R, et al. An evaluation of the 1954 poliomyelitis vaccine trials–Summary report. Amer J Public Health Nations Health. 1955;45(5 Pt 2):1-63. DOI: 10.1177/1740774511399110.
83. Bourne PA, Hudson-Davis A. Psychiatric induced births in Jamaica: homicide and death effects on pregnancy. Psychol Behav Sci Int J. 2016;1(1): 6 p. DOI: 10.19080/PBSIJ.2016.01.555558.
84. Mukaka MM. Statistics corner: A guide to appropriate use of correlation coefficient in medical research. Malawi Med J. 2012;24(3):69-71.
85. Schober P, Boer C, Schwarte L.A. Correlation coefficients: appropriate use and interpretation. Anesth Analg. 2018;126(5):1763-68. DOI: 10.1213/ANE.0000000000002864.
86. Rule of thumb for interpreting the size of a correlation coefficient. %20al.pdf (Address data 2019.01.30).
87. Pearson correlation coefficient achieves value from 1. Site Int Islamic University Malaysia. (Address data 2019.01.30).
88. Kotrlik JW, Williams HA, Jabor MK. Reporting and interpreting effect size in quantitative agricultural education research. J Agricult Edu. 2011;52(1):132-42. DOI: 10.5032/jae.2011.01132.
89. Hinkle DE, Wiersma W, Jurs SG. Applied Statistics for the Behavioral Sciences. – Chicago: Rand McNally College Pub. Co. 1979. 479 p.
90. Hinkle DE, Wiersma W, Jurs SG. Applied Statistics for the Behavioral Sciences. 5th Ed. – Boston: Houghton Mifflin. 2003. 756 p.
91. Correlation Coefficients. Applied Statistics – Lesson 5. Andrews University (Michigan). 2005. (Address data 2019.01.30).
92. Moore D. The Basic Practice of Statistics. 6th Ed. Ed. by D. Moore, W.I. Notz, M.A. Fligner. Publisher: W.H. Freeman, 2012. 989 p.
93. Rumsey DJ. Statistics For Dummies. 2nd Ed. – New York: For Dummies, 2016. 411 p.
94. Evans JD. Straightforward statistics for the behavioral sciences. – Pacific Grove, Calif.: Brooks/Cole Publ. Co: An International Thomson Publ. Co, 1996. 624 p.
95. Chakkapark J, Vinitwatanakun W. The relationship between division heads’ leadership styles and teacher satisfaction at Siam Commercial College of Technology. Scholar: Hum Sci. 2017;9(1):36-47.
96. Miletic M, Vukusic M, Mausa G, Galinac T. Relationship between design and defects for software in evolution. In: Proceedings of the SQAMIA 2017: 6th Workshop of Software Quality, Analysis, Monitoring, Improvement, and Applications. Ed. by Z. Budimac. – Belgrade, Serbia, 11-13.9.2017. (Address data 2019.01.30).
97. Gerguri D. Leader-staff relationships in Kosovo customs: leadership and its impact on customs effectiveness. Styles of Communication. 2018;10(1):108-24. (Address data 2019.01.30).
98. Pearson’s correlation. Site Statstutor. Statistics support for students. UK. (Address data 2019.01.30).
99. Buhl A, Zofel P. SPSS Version 10. 7th revised & extended Ed. – Munchen etc: Addison Wesley Bunnel D, 2000.
100. Grjibovski AM, Ivanov SV, Gorbatova MA. Correlation analysis of data using Statistica and SPSS software. Nauka i Zdravookhranenie (Science & Healthcare). 2017(1):7-36. (Address data 2019.01.30). (In Russian; English abstract.)
101. Pearson and Spearman correlation coefficients. Training material. The site of K.D. Ushinsky Yaroslavl State Pedagogical University.Тема_5_Коэффициенты_корреляции_Пирсона_и_Спирмена.pdf (Address data 2019.01.30). (In Russian).
102. Pearson Product-Moment Correlation. In site: ‘We make statistics easy. The ultimate IBM SPSS Statistics guides’. (Address data 2019.01.30).
103. Interpreting r. CSU Department of Statistics. 2014. (Address data 2019.01.30).
104. Karadimitriou SM. Correlation in R. Statstutor Community Project. University of Sheffield.!/file/MASH_Correlation_R.pdf (Address data 2019.01.31).
105. Gerstman BB. Correlation. StatPrimer (Version 7.0). Faculty websites inside. 2016. (Address data 2019.01.31).
106. Kharchenko MA. Correlation Analysis. Textbook for Universities. – Voronezh: Publishing and Printing Center of the Voronezh State University, 2008. 31 p. (In Russian).
107. Hopkins WG. A new view of statistics. A scale of magnitudes for effect statistics. 2002. (Address data 2019.02.01).
108. Bruce N, Pope D, Stanistreet D. Quantitative Methods for Health Research. A Practical Interactive Guide to Epidemiology and Statistics. 2nd Ed. – Oxford: John Wiley & Sons, 2019. 545 p.
109. Jackson SL. Statistics Plain and Simple, 2nd Ed. – Belmont, CA: Cengage/Wadsworth, 2009. 377 p.
110. Dancey CP, Reidy J. Statistics without Maths for Psychology. 4th Ed. – Harlow: Pearson Education Limited, 2007. 619 p.
111. Akoglu H. User’s guide to correlation coefficients. Turk J Emerg Med. 2018;18(3):91-3. DOI: 10.1016/j.tjem.2018.08.001.
112. Chan YH. Biostatistics 104: correlational analysis. Singap Med J. 2003;44(12):614-9.
113. Koterov AN. From very low to very large doses of radiation: new data on ranges definitions and its experimental and epidemiological basing. Medical Radiology and Radiation Safety (Moscow). 2013;58(2):5-21. (In Russian. English abstract).
114. Burnand B, Kernan WN, Feinstein AR. Indexes and boundaries for “quantitative significance” in statistical decisions. J Clin Epidemiol. 1990;43(12):1273-1284. DOI: 10.1016/0895-4356(90)90093-5.
115. Kline PA. Handbook of Test Construction. – London: Routledge, 1987. 250 p.
116. Kline PA. A Handbook of Test Construction. Introduction to Psychometric Design. – London and New York: Routledge Taylor & Francis Group, 2015. 259 p.
117. Spearman’s Correlation. Site Statstutor. UK. (Address data 2019.02.01).
118. McGhee RL, Ehrler DJ, Buckhalt JA, Phillips C. The relation between five-factor personality traits and risk-taking behavior in preadolescents. Psychology. 2012;3(8):558-61. DOI: 10.4236/psych.2012.38083.
119. Reinard JC. Communication Research Statistics. – SAGE Publications, 2006. 600 p.
120. Koterov AN, Zharkova GP, Biryukov AP. Tandem of radiation epidemiology and radiobiology for practice and radiation protection. Medical Radiology and Radiation Safety (Moscow). 2010; 55(5):48-73. (In Russian. English abstract).
121. Biryukov AP, Vasil’ev EV, Dumansky SM, Belyikh LN. Information-analytical support for radiation-epidemiological research activities. Medical Radiology and Radiation Safety (Moscow). 2014; 59(6):34-42. (In Russian. English abstract).

For citation: Koterov AN, Ushenkova LN, Zubenkova ES, Kalininna MV, Biryukov AP, Lastochkina EM, Molodtsova DV, Wainson AA. Strength of association. Report 2. Graduation of correlation size. Medical Radiology and Radiation Safety. 2019;64(6):12–24. (In Russian)

DOI: 10.12737/1024-6177-2019-64-6-12-24

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