相关实验视频
Updated: May 21, 2025

09:36
Assessment of Swim Endurance and Swim Behavior in Adult Zebrafish
Published on: November 12, 2021
3.1K
法国游泳运动员中学的生存分析
Audrey Difernand1,2, Alexia Mallet1,2, Quentin De Larochelambert1,2
1IRMES-URP 7329, Institut de Recherche Médicale et d'Epidémiologie du Sport, Université Paris Cité, Paris, France.
Frontiers in sports and active living
|March 20, 2025
概括
法国游泳运动员在表现较低的情况下,失学率更高. 女游泳运动员的学率高于男游泳运动员,特别是在13岁以后,受相对年龄和出生季度的影响.
科学领域:
- 运动科学 运动科学 运动科学
- 青少年体育分析 青少年体育分析
- 人才发展 人才发展
背景情况:
- 运动员退出是青少年体育的一个重大问题.
- 了解影响中断的因素对于人才保留和计划开发至关重要.
- 相对年龄和性别是公认的人口因素,可能会影响运动轨迹.
研究的目的:
- 调查性能水平,性别和相对年龄对法国游泳运动员中学率的影响.
- 为了确定特定的年龄点和与增加学风险相关的人口差异.
- 分析一大批年轻游泳者的出生季度,表现和磨损之间的相互作用.
主要方法:
- 对21岁以下的法国游泳运动员的大量数据集 (160,861) 的分析.
- 使用奇二测试来评估出生季度对表现的影响.
- 采用卡普兰-梅尔生存率 (KMS) 曲线来评估按性别和相对年龄的学趋势.
主要成果:
- 在所有年龄组中,表现较差的游泳者中,学率显著更高.
- 在女性中被确定为13.16岁,在男性中被确定为17.50岁.
- 与男性相比,女性游泳者在13岁后的学率增加得更快.
- 与出生季度相关的学业学率的差异很明显,在12.7岁 (女孩) 和14.7岁 (男孩) 左右达到顶峰.
结论:
- 绩效水平,性别和相对年龄是青少年游泳中断的关键决定因素.
- 女游泳者面临更高的消耗率,特别是在晚年青春期.
- 旨在减少中断的干预措施应考虑这些人口和绩效相关因素.
相关概念视频
Censoring Survival Data
55
Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different...
55
Assumptions of Survival Analysis
77
Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
77
Comparing the Survival Analysis of Two or More Groups
110
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
110
Truncation in Survival Analysis
142
Truncation in survival analysis refers to the exclusion of individuals or events from the dataset based on specific criteria related to the time of the event. This exclusion can happen in two primary forms: left truncation and right truncation.
Left truncation occurs when individuals who experienced the event of interest before a certain time are not included in the study. This is often due to a "delayed entry" into the study where only those who survive until a certain entry point are...
Left truncation occurs when individuals who experienced the event of interest before a certain time are not included in the study. This is often due to a "delayed entry" into the study where only those who survive until a certain entry point are...
142
Introduction To Survival Analysis
147
Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.
The primary goal of survival analysis is to estimate survival time—the time...
The primary goal of survival analysis is to estimate survival time—the time...
147
Cancer Survival Analysis
315
Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
315

