Table 5

Evaluation of the degree to which authors’ use of statistical tools addressed theoretical and temporal design challenges

MethodnThemes of theoretical modelThemes of temporal design—intensive longitudinal data
Multifactorial aetiologyBetween-athlete and within-athlete differencesComplex systemIncludes time-varying and time-invariant variablesMissing/unbalanced data*Repeated measure dependencyIncorporates time into the analysis
Correlation (Pearson and Spearman)10XXXXXXX
Unpaired t-test6XXXXXXX
Relative risk calculations8OXXXXXX
Regression (logistic, linear, multinomial)13OXXXXXX
Paired t-test2XXXXX
Repeated measures ANOVA
(one-way or two-way)
Generalised estimating equations
(Poisson and logistic)
Cox proportional hazards model1XXX
Multilevel modelling1XX
Frailty model1X
  • Qualitative assessment performed on a three-tiered scale. An ‘X’ (red formatting) means that none of the authors using this tool adequately addressed that specific challenge. In some cases, this may be because the statistical model was unable to address it, and other times it may be because of the way they used it. An ‘O’ (yellow formatting) indicates that some authors addressed that challenge while others did not. This generally happened when the statistical tool could address a challenge but the authors sometimes chose not to use it in that way. A ‘✓’ (green formatting) indicates that all authors using this statistical tool addressed that challenge adequately.

  • *Missing/unbalanced data here is that caused by intensive longitudinal data—meaning a different number of observations for each athlete during the observation period, some of which may be missing.

  • ANOVA, analysis of variance.