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Missing data: current practice in football research and recommendations for improvement
David N Borg1,2, Robert Nguyen3, Nicholas J Tierney4,5
1Menzies Health Institute Queensland, The Hopkins Centre, Griffith University, Brisbane, Australia.
Methods:
A survey of 136 articles published in 2019 (sampled at random) was conducted to determine whether a statement about missing data was included.
Results:
The proportion of studies reporting on missing data was low, at 11.0% (95% confidence interval = 6.3% to 17.5%).
Recommendations:
We recommend that researchers describe the number and percentage of missing values, including when there are no missing values. Exploratory analysis should be conducted to explore missing values, and visualisations describing missingness overall should be provided in the paper, or at least in supplementary materials. Missing values should almost always be imputed, and imputation methods should be explored to ensure they are appropriately representative. Researchers should consider these recommendations and pay greater attention to missing data and its influence on research results.
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