Korean J Pain.  2017 Oct;30(4):243-249. 10.3344/kjp.2017.30.4.243.

Practical statistics in pain research

• Kim TK

• KMID: 2392900
• DOI: http://doi.org/10.3344/kjp.2017.30.4.243

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.

Keyword

Analysis of variance; Biostatistics; Nonparametric; Normal distribution; Pain measurement; Visual analog scale

MeSH Terms

Analysis of Variance
Biostatistics
Normal Distribution
Pain Measurement
Visual Analog Scale
Weights and Measures

Figure

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  Fig. 1 Comparison of the heights between the children who stand on different level of stairs is difficult. The stairs would stand for the relationship between repeated measurements in RMANOVA, which could make it difficult to compare the height directly (A). Once the level of stairs gets even, it would make it easier to compare the heights (B).

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  Fig. 2 The correlation coefficients between repeated measurements are presented in a manner of table. The coefficient of diagonal parts should be 1 due to correlation by itself. If the coefficients of off-diagonal parts are same for all, it can be announced that the sphericity assumption is satisfied. Maucley's sphericity test is one of the frequently used sphericity assumption tests.

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  Fig. 3 To know the differences of height within subject as students grow up, RMANOVA is available and the sphericity assumption should be guaranteed. To compare within subject factor which means the differences between each grades, paired comparisons between the grades could be done with adjustment of significance level like the Bonferroni's correction. To compare the between subject factor at each grade, paired comparisons could be done with significance levels adjusted by like the Bonferroni's procedure.

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