Table 4

The number of studies using various statistical analysis techniques

Analytical methodN
Regression modelling
 Logistic
  Regular10
  Generalised estimating equation5
  Multilevel1
 Linear 2
  Regular
 Poisson 
  Generalised estimating equation*1
 Multinomial regression
  Regular1
 Cox proportional hazards model1
 Frailty model1
Correlation
 Pearson9
 Spearman1
Relative risk/rate ratio†8
T-tests
 Paired and independent samples4
 Independent samples only2
Χ2 tests1
Repeated measures ANOVA (one-way or two-way)5
  • If articles used more than one statistical method to analyse workload and injury, they are included more than once in the table. We only report analyses used to analyse workload–injury associations, not other analyses reported in the articles (eg, ANOVA to test for differences in total workloads at separate times of the season).

  • *Clausen et al 39 also report fitting multilevel models, but do not report any of the results—presenting only their GEE findings in their results and discussion.

  • †Relative risk here refers to the use of RR as a primary analysis based on risks in different categorical groups, not as an effect estimated from another model. For example, comparing risks among different load groups like Hulin et al 33 47 are counted here, whereas Gabbett and Ullah66 derived RR from their frailty model, and Clausen et al 39 derived RR from their Poisson model, but neither are included in the count for RR.

  • ANOVA, analysis of variance; GEE, generalised estimating equation.