数据链接：
官方服务：
资源简介：
Swimmers’ characteristics (data are means ± SE).
应用场景：
创建时间：
2017-09-09
相关数据集
The raw datasets and statistics for each analysis result graph.
Each individual result graph is associated with 4 different comma-separated files: (i) Raw—the (anonymised) raw data behind the means and standard deviations used for a particular result graph; (ii) P
NIAID Data Ecosystem70
Average consensus, standard deviations, and range for the 24 S8* items, aggregated across all sports.
Average consensus, standard deviations, and range for the 24 S8* items, aggregated across all sports.
Figshare2020-10-22 更新10
Between-group comparisons of changes in all performance measures, from PRE-to-MID and PRE-to-POST training.
Data are mean percent differences and 90% compatibility intervals (±90%CI), plus magnitude-based decisions of standardised effect sizes (ES) and qualitative likelihoods†.
Figshare2020-05-14 更新00
Univariable and multivariable binary logistic regression analysis of sport-related factors and personal characteristics.
Univariable and multivariable binary logistic regression analysis of sport-related factors and personal characteristics.
NIAID Data Ecosystem10
Intercepts and slopes, and respective standard errors (SE) and 95% confidence limits based on the weighted Deming regression of predicted ages at PHV (y-axis) and observed (actual) ages at PHV (x-axis) for the Mirwald and Moore prediction equations at each observation (Obs) in youth soccer players * .
Intercepts and slopes, and respective standard errors (SE) and 95% confidence limits based on the weighted Deming regression of predicted ages at PHV (y-axis) and observed (actual) ages at PHV (x-axis
NIAID Data Ecosystem10
