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

Quantifying and Rejecting Outliers: The Grubbs Test01:02

Quantifying and Rejecting Outliers: The Grubbs Test

1.5K
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...
1.5K
Truncation in Survival Analysis01:09

Truncation in Survival Analysis

171
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...
171
Contingency Table01:29

Contingency Table

2.4K
A contingency table provides a way of portraying data that can facilitate calculating probabilities. It is a method of displaying a frequency distribution as a table with rows and columns to show how two variables may be dependent (contingent) upon each other; The table helps determine conditional probabilities quite quickly and can help systematically organize, analyze and quantify data. The table displays sample values concerning two variables that may be dependent or contingent on one...
2.4K
Prediction Intervals01:03

Prediction Intervals

2.2K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y. 
2.2K
Assumptions of Survival Analysis01:15

Assumptions of Survival Analysis

99
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.
99
What Are Outliers?01:12

What Are Outliers?

3.6K
Outliers are observed data points that are far from the least squares line. They have unusual values and need to be examined carefully. Though an outlier may result from erroneous data, at other times, it may hold valuable information about the population under study and should be included in the data. Hence, it is crucial to examine what causes a data point to be an outlier.
The z score is used to find outliers or unusual values. It should be noted that any values beyond -2 and +2 are...
3.6K

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

Association of Glucagon-Like Peptide-1 Receptor Agonists With Menstrual Events in Reproductive-Aged Patients.

Obstetrics and gynecology·2026
Same author

Association of ciltacabtagene autoleucel with immune effector cell-associated enterocolitis: insights from a large national database.

Blood cancer journal·2026
Same author

Realistic presentation of estimated propensity score in the causal directed acyclic graph-response to Kim.

International journal of epidemiology·2026
Same author

Glucagon-Like Peptide-1 Receptor Agonists and Cancer.

JAMA oncology·2025
Same author

Incorrect Conclusions From Misinterpreting Point Estimates and CIs.

JAMA ophthalmology·2025
Same author

Balancing scores and causal diagrams.

International journal of epidemiology·2025

相关实验视频

Updated: Jun 11, 2025

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

14.4K

一个关于处理条件缺失值的说明.

Mohammad Ali Mansournia1, Maryam Nazemipour1, Mahyar Etminan2

  • 1Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.

Global epidemiology
|October 9, 2024
PubMed
概括

医学研究中的有条件缺失数据需要归算,以避免不高效的列表删除. 简单的归算方法可以有效地处理这些结构性缺失值在病因学和预测研究.

科学领域:

  • 医学研究 医学研究
  • 生物统计学 生物统计学
  • 流行病学 流行病学

背景情况:

  • 数据缺失是医学研究中一个常见的挑战.
  • 当一个变量的定义取决于另一个变量的级别时,有条件的缺失数据就会出现.
  • 列表式删除是处理回归分析中缺少数据的低效方法.

研究的目的:

  • 解决因条件变量定义造成的结构性缺失数据的问题.
  • 为了说明处理条件缺失值的简单归算程序.
  • 提高病因和预测研究数据分析的效率.

主要方法:

  • 用实际例子说明条件缺失数据场景.
  • 应用简单的归算技术来解决结构缺失的问题.
  • 将归算方法与回归建模中的列表式删除进行比较.

主要成果:

  • 证明了简单的归算方法可以有效地处理条件缺失数据.
  • 在存在结构性缺失的情况下,展示了按列表删除的无效性.
  • 提供了在医学研究中实施归算的实际指导.

结论:

更多相关视频

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

7.5K
Using Continuous Data Tracking Technology to Study Exercise Adherence in Pulmonary Rehabilitation
09:42

Using Continuous Data Tracking Technology to Study Exercise Adherence in Pulmonary Rehabilitation

Published on: November 8, 2013

13.5K

相关实验视频

Last Updated: Jun 11, 2025

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

14.4K
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

7.5K
Using Continuous Data Tracking Technology to Study Exercise Adherence in Pulmonary Rehabilitation
09:42

Using Continuous Data Tracking Technology to Study Exercise Adherence in Pulmonary Rehabilitation

Published on: November 8, 2013

13.5K
  • 简单的归算程序是管理医学研究中条件缺失数据的宝贵工具.
  • 有效处理结构性缺失数据可以提高病因和预测模型的准确性和效率.
  • 该研究强调了对不完整数据集采用适当统计方法的重要性.