Received: NovemAccepted: JPublished: July 11, 2018Ĭopyright: © 2018 Knechtle et al. PLoS ONE 13(7):Įditor: Luca Paolo Ardigò, Universita degli Studi di Verona, ITALY To study a potential difference between races at home and races abroad, an interaction term race site home/abroad with nationality was included in the model.Ĭitation: Knechtle B, Nikolaidis PT, Valeri F (2018) Russians are the fastest 100-km ultra-marathoners in the world. In addition to the linear regression a truncated regression was performed with the truncated dataset to allow conclusion for the whole sample. From the complete dataset the finishes with more than 14 hours were removed (truncated dataset) and the same descriptive plots and analysis as for the complete dataset were performed again. Histograms, density and scatter plots showed that some races seemed to have a time limit of 14 hours. A linear regression analysis adjusted by sex, age and year was performed to study the race time between the nationalities. Crude mean, standard deviation, median, interquartile range (IQR), mode, skewness and excess of time for each nationality were computed. Histograms and density plots were performed to study the distribution of race time. To get precise estimates and stable density plots we selected only those nationalities with 900 and more finishes resulting in 24 nationalities. We analysed data from 150,710 athletes who finished a 100-km ultra-marathon between 19.
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