Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Censoring Survival Data01:09

Censoring Survival Data

134
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...
134
Quantifying and Rejecting Outliers: The Grubbs Test01:02

Quantifying and Rejecting Outliers: The Grubbs Test

1.7K
Sometimes, a data set can have a recorded numerical observation that greatly  deviates from the rest of the data. Assuming that the data is normally distributed, a statistical method called the Grubbs test can be used to determine whether the observation is truly an outlier.  To perform a two-tailed Grubbs test, first, calculate the absolute difference between the outlier and the mean. Then, calculate the ratio between this difference and the standard deviation of the sample. This...
1.7K
Self-Presentation: Self-Monitoring and Self-Handicapping02:05

Self-Presentation: Self-Monitoring and Self-Handicapping

39.1K
People can go to great lengths to protect their self-image and present themselves in ways that they want others to see them. Sociologist Erving Goffman presented the idea that a person is like an actor on a stage. Calling his theory dramaturgy, Goffman believed that we use “impression management” to present ourselves to others as we hope to be perceived. Each situation is a new scene, and individuals perform different roles depending on who is present (Goffman, 1959). Think about...
39.1K
Clearance Models: Noncompartmental Models01:17

Clearance Models: Noncompartmental Models

79
Clearance is a pharmacokinetic parameter traditionally defined by compartment models, signifying the rate at which a drug is expelled from the body. However, a noncompartmental model offers an alternative method for assessing clearance, primarily employing empirical data obtained after administering a single drug dose.
The noncompartmental approach capitalizes on extensive sampling data, correlating the volume of distribution to systemic exposure and the administered dosage. This method enables...
79
Truncation in Survival Analysis01:09

Truncation in Survival Analysis

237
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...
237
Stereotype Content Model02:16

Stereotype Content Model

14.8K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
14.8K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Separability and identifiability as primary obstacles to substantively useful mediation analysis.

European journal of epidemiology·2026
Same author

Instrumental Variable Estimation of Marginal Structural Mean Models for Time-Varying Treatment.

Journal of the American Statistical Association·2026
Same author

Age-specific disparities in rural and urban survival among patients with IDH-wildtype glioblastoma: a population-based study.

Cancer causes & control : CCC·2026
Same author

Finding distributions that differ, with false discovery rate control.

Biometrika·2026
Same author

Development and Validation of Machine Learning Models to Identify Emergency Department Patients at Increased Risk of New or Progressive Acute Kidney Injury.

Journal of the American College of Emergency Physicians open·2026
Same author

Ultrasensitive and multi-analyte detection of catecholamines in serum and cerebrospinal fluid using carboxyl-modified magnetic microspheres coupled with LC/MS.

Journal of chromatography. A·2026

相关实验视频

Updated: Jul 22, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
04:57

Establishing a Competing Risk Regression Nomogram Model for Survival Data

Published on: October 23, 2020

10.2K

对于多变量非可忽视的非单调的缺失数据的自我审查模型.

Yilin Li1, Wang Miao1, Ilya Shpitser2

  • 1Department of Probability and Statistics, Peking University, Beijing, China.

Biometrics
|July 25, 2023
PubMed
概括

我们开发了"自我审查",这是一个新的统计模型,用于处理多个变量的复杂缺失数据. 这种方法提高了多变量非可忽略的非单调的缺失数据的分析准确性.

关键词:
这是一个双重可靠的估计.标识 标识 标识 标识 标识失踪并不是随机发生的.非单调的缺失性 缺失性

更多相关视频

Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients
07:34

Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients

Published on: August 22, 2018

8.3K
Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits
08:27

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits

Published on: September 27, 2019

6.9K

相关实验视频

Last Updated: Jul 22, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
04:57

Establishing a Competing Risk Regression Nomogram Model for Survival Data

Published on: October 23, 2020

10.2K
Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients
07:34

Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients

Published on: August 22, 2018

8.3K
Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits
08:27

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits

Published on: September 27, 2019

6.9K

科学领域:

  • 统计 统计 统计 统计
  • 生物统计学 生物统计学
  • 流行病学 流行病学

背景情况:

  • 多变量数据经常表现出复杂的缺失模式.
  • 不能忽视的和不单调的缺失数据带来了重大的分析挑战.
  • 现有的图形方法可能无法完全解决这些复杂性.

研究的目的:

  • 为了引入一种新的项目级建模方法,
  • 自我审查的自我审查.
  • ,对于多变量非可忽略的非单调的缺失数据.
  • 提供半参数估计器和全球灵敏度分析程序.
  • 在现实世界健康研究中展示自我审查模型的实用性.

主要方法:

  • 开发了"自我审查"模型,其中每个结果的缺失取决于其自身价值和其他结果的缺失指标.
  • 建议用于参数估计的半参数和双重可靠的估计器.
  • 引入了一个针对自我审查模型的全球敏感性分析程序.
  • 通过模拟研究验证的方法和对HIV/ART数据的应用.

主要成果:

  • 自我审查模型是在完整性条件下确定的.
  • 双重可靠的估计器确保有效的推断,即使部分模型的错误规范.
  • 敏感性分析提供了一个灵活的工具来评估缺失数据的影响.
  • 该模型已成功应用于分析高活性抗逆转录病毒疗法对早产产生的影响.

结论:

  • 自我审查方法为分析多变量非可忽视的非单调的缺失数据提供了强大的框架.
  • 提出的估计和灵敏度分析方法是有效和灵活的.
  • 这种方法提高了复杂的健康相关数据集的分析.