bioRxivSystems BiologyPreprint
Assessing the statistical reporting quality in high-impact factor urology journals
ShuangYang Dai, Hong Wei XuiD, Beibei LiiD, Jingao Zhang, Xiaobin ZhouiD
Abstract
BackgroundsObservational studies plays an important role in urology studies, But few studies have paid attention to the statistical reporting quality of observational studies. The purpose of this study was to investigate the frequency and evaluate the reporting quality of statistical methods of the published observational studies in urology. MethodsThe five urology journals were selected according to the 5-year impact factor. A systematic literature search was performed in PubMed for relevant articles. The quality of statistical reporting was assessed according to assessment criteria. ResultsA total of 193 articles were included in this study. The mean statistical reporting score of included articles was 0.42 (SD=0.15), accounting for 42% of total score. The items that must be reported with a reporting rate more than 50% were: alpha level (n=122, 65.2%), confidence intervals (n=134, 69.4%), name of statistical package (n=158, 84.5%) and exact P-values (n=161, 86.1%). The items with a reporting rate less than 50% were: outliers (n=2, 1.0%) and sample size (n=13, 6.7%). For multivariable regression models (liner, logistic and Cox), variables coding (n=27, 40.7%), validation analysis of assumptions (n=58, 40.3%), interaction test (n=43, 30.0%), collinearity diagnostics (n=5, 3.5%) and goodness of fit test (n=6, 5.9%) were reported. Number of authors more than 7(OR=2.06, 95%CI=1.04-4.08) and participation of statistician or epidemiologist (OR=1.73, 95%CI=1.18-3.39) were associated with the superior reporting quality. ConclusionThe statistical reporting quality of published observational studies in 5 high-impact factor urological journals was alarming. We encourage researchers to collaborate with statistician or epidemiologist. The authors, reviewers and editors should increase their knowledge of statistical methods, especially new and complex methods.
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