{"title":"Missing data: current practice in football research and recommendations for improvement","authors":"D. Borg, Robert Nguyen, Nicholas J. Tierney","doi":"10.1080/24733938.2021.1922739","DOIUrl":null,"url":null,"abstract":"ABSTRACT 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.","PeriodicalId":48512,"journal":{"name":"Science and Medicine in Football","volume":null,"pages":null},"PeriodicalIF":2.8000,"publicationDate":"2020-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24733938.2021.1922739","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Science and Medicine in Football","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/24733938.2021.1922739","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"SPORT SCIENCES","Score":null,"Total":0}
引用次数: 13
Abstract
ABSTRACT 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.