Related Experiment Video
Updated: Oct 16, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Prediction of Distance Running Performances of Female Runners Using Nomograms
Lucie Lerebourg1, Brice Guignard1, Ghazi Racil2
1UFR STAPS, CETAPS, Université de Rouen-Normandie, Mont-Saint-Aignan, France.
Abstract:
This study examined the validity, precision and accuracy of the predictions of distance running performances in female runners from three nomograms. Official rankings of French women for the 3000-m, 5000-m, and 10 000-m track-running events from 2005 to 2019 were examined. Only female runners who performed in the three distance events within the same year were included (n=158). Each performance over any distance was predicted using the three nomograms from the two other performances. The 3000-m, 5000-m and 10 000-m performances were 11min17 s±1min20 s, 19min29 s±2min20 s, 41min18 s±5min7 s, respectively. No difference was found between the actual and predicted running performances regardless of the nomogram (p>0.05). All predicted running performances were significantly correlated with the actual ones, with a very high correlation coefficient (p<0.001; r>0.90). Bias and 95% limits of agreement were acceptable because, whatever the nomogram, they were less than or equal to - 0.0±6.2% on the 3000-m, 0.0±3.7% on the 5000-m, and 0.1±9.3% on the 10 000-m. The study confirms the validity of the three nomograms to predict track-running performance with a high level of accuracy. The predictions from these nomograms are similar and may be used in training programs and competitions.
More Related Videos
08:26Comparative Analysis of Lower Limb Kinematics between the Initial and Terminal Phase of 5km Treadmill Running
Published on: July 17, 2020
06:46Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
Related Concept Videos
Dosage Regimen Designs: Nomograms and Tabulations
Construction of Frequency Distribution
First, make a table with two columns—one with the title of the data that needs to be organized, and the other column for frequency. [Draw a third column for tally marks if needed]. Then, take a look at the items given in the data set and decide if an ungrouped frequency distribution table or a grouped frequency distribution table would be more suitable. If there are large sets of different values, then it is...
Interpreting Run Charts
Wald-Wolfowitz Runs Test I
The test works...
Run Charts
Wald-Wolfowitz Runs Test II
For binary data, runs are identified using symbols such as + and −, or equivalently, 1s and...