The Korean Journal of Pain

The Korean Pain Society (대한통증학회)
권호 표지
DOI QR코드

DOI QR Code

Practical statistics in pain research

  • Kim, Tae Kyun (Department of Anesthesia and Pain Medicine, Pusan National University School of Medicine)
  • Received : 2017.09.07
  • Accepted : 2017.09.13
  • Published : 2017.10.01
Download PDF
⟨ Previous Next ⟩

Abstract

Pain is subjective, while statistics related to pain research are objective. This review was written to help researchers involved in pain research make statistical decisions. The main issues are related with the level of scales that are often used in pain research, the choice of statistical methods between parametric or nonparametric statistics, and problems which arise from repeated measurements. In the field of pain research, parametric statistics used to be applied in an erroneous way. This is closely related with the scales of data and repeated measurements. The level of scales includes nominal, ordinal, interval, and ratio scales. The level of scales affects the choice of statistics between parametric or non-parametric methods. In the field of pain research, the most frequently used pain assessment scale is the ordinal scale, which would include the visual analogue scale (VAS). There used to be another view, however, which considered the VAS to be an interval or ratio scale, so that the usage of parametric statistics would be accepted practically in some cases. Repeated measurements of the same subjects always complicates statistics. It means that measurements inevitably have correlations between each other, and would preclude the application of one-way ANOVA in which independence between the measurements is necessary. Repeated measures of ANOVA (RMANOVA), however, would permit the comparison between the correlated measurements as long as the condition of sphericity assumption is satisfied. Conclusively, parametric statistical methods should be used only when the assumptions of parametric statistics, such as normality and sphericity, are established.

Keywords

References

  1. Yim KH, Nahm FS, Han KA, Park SY. Analysis of statistical methods and errors in the articles published in the Korean Journal of Pain. Korean J Pain 2010; 23: 35-41. https://doi.org/10.3344/kjp.2010.23.1.35
  2. Norman G. Likert scales, levels of measurement and the “laws” of statistics. Adv Health Sci Educ Theory Pract 2010; 15: 625-32. https://doi.org/10.1007/s10459-010-9222-y
  3. Huskisson EC. Measurement of pain. J Rheumatol 1982; 9: 768-9.
  4. Price DD, McGrath PA, Rafii A, Buckingham B. The validation of visual analogue scales as ratio scale measures for chronic and experimental pain. Pain 1983; 17: 45-56. https://doi.org/10.1016/0304-3959(83)90126-4
  5. Dexter F, Chestnut DH. Analysis of statistical tests to compare visual analog scale measurements among groups. Anesthesiology 1995; 82: 896-902. https://doi.org/10.1097/00000542-199504000-00012
  6. Nunnally JC, Bernstein IH. Psychometric theory. 3rd ed. New York (NY), McGraw-Hill Book Company. 1994, p 115.
  7. Heeren T, D'Agostino R. Robustness of the two independent samples t-test when applied to ordinal scaled data. Stat Med 1987; 6: 79-90. https://doi.org/10.1002/sim.4780060110
  8. Sullivan LM, D'Agostino RB Sr. Robustness and power of analysis of covariance applied to ordinal scaled data as arising in randomized controlled trials. Stat Med 2003; 22: 1317-34. https://doi.org/10.1002/sim.1433
  9. Lee Y. What repeated measures analysis of variances really tells us. Korean J Anesthesiol 2015; 68: 340-5. https://doi.org/10.4097/kjae.2015.68.4.340
  10. Kim TK. Understanding one-way ANOVA using conceptual figures. Korean J Anesthesiol 2017; 70: 22-6. https://doi.org/10.4097/kjae.2017.70.1.22
  11. Bland JM, Altman DG. Multiple significance tests: the Bonferroni method. BMJ 1995; 310: 170. https://doi.org/10.1136/bmj.310.6973.170
  12. Rothman KJ. No adjustments are needed for multiple comparisons. Epidemiology 1990; 1: 43-6. https://doi.org/10.1097/00001648-199001000-00010
  13. Perneger TV. What's wrong with Bonferroni adjustments. BMJ 1998; 316: 1236-8. https://doi.org/10.1136/bmj.316.7139.1236
  14. Glickman ME, Rao SR, Schultz MR. False discovery rate control is a recommended alternative to Bonferroni-type adjustments in health studies. J Clin Epidemiol 2014; 67: 850-7. https://doi.org/10.1016/j.jclinepi.2014.03.012

Cited by

  1. Core Outcome Measures in Preclinical Assessment of Candidate Analgesics vol.71, pp.2, 2017, https://doi.org/10.1124/pr.118.017210
  2. Patients’ Perspective on Carpal Tunnel Release with WALANT or Intravenous Regional Anesthesia vol.145, pp.5, 2017, https://doi.org/10.1097/prs.0000000000006741
  3. The effects of whole-body electromyostimulation (WB-EMS) in comparison to a multimodal treatment concept in patients with non-specific chronic back pain—A prospective clinical intervention stud vol.15, pp.8, 2020, https://doi.org/10.1371/journal.pone.0236780
  4. Pain scores and statistical analysis-the conundrum vol.12, pp.1, 2017, https://doi.org/10.1186/s42077-020-00085-8
  5. Inter‐observer variability of two grading systems for equine glandular gastric disease vol.53, pp.3, 2021, https://doi.org/10.1111/evj.13334
  6. Coolsense® versus EMLA® for peripheral venous cannulation in adult volunteers: A randomised crossover trial vol.49, pp.6, 2021, https://doi.org/10.1177/0310057x211039227
  7. Evaluation of analgesic interaction between morphine, maropitant and dexmedetomidine in dogs undergoing ovariohysterectomy vol.70, pp.1, 2017, https://doi.org/10.1080/00480169.2021.1927231