Table 5.

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

Method	n	Themes of theoretical model			Themes of temporal design—intensive longitudinal data
		Multifactorial aetiology	Between-athlete and within-athlete differences	Complex system	Includes time-varying and time-invariant variables	Missing/unbalanced data*	Repeated measure dependency	Incorporates time into the analysis
Correlation (Pearson and Spearman)	10	X	X	X	X	X	X	X
Unpaired t-test	6	X	X	X	X	X	X	X
Χ2 test	1	X	X	X	X	X	X	X
Relative risk calculations	8	O	X	X	X	X	X	X
Regression (logistic, linear, multinomial)	13	O	X	X	X	X	X	X
Paired t-test	2	X	X	X	X	X	✓	✓
Repeated measures ANOVA (one-way or two-way)	5	O	O	X	O	X	✓	✓
Generalised estimating equations (Poisson and logistic)	6	O	X	X	O	✓	✓	O
Cox proportional hazards model	1	✓	X	X	X	✓	✓	✓
Multilevel modelling	1	✓	✓	X	✓	✓	✓	X
Frailty model	1	✓	✓	X	✓	✓	✓	✓

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.