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

Confounding in Epidemiological Studies01:27

Confounding in Epidemiological Studies

586
Confounding in statistical epidemiology represents a pivotal challenge, referring to the distortion in the perceived relationship between an exposure and an outcome due to the presence of a third variable, known as a confounder. This variable is associated with both the exposure and the outcome but is not a direct link in their causal chain. Its presence can lead to erroneous interpretations of the exposure's effect, either exaggerating or underestimating the true association. This...
586
Confidence Interval for Estimating Population Mean01:25

Confidence Interval for Estimating Population Mean

8.7K
A point estimate of the population mean is obtained from a single sample. Such a point estimate does not represent a population well because it needs to account for variability in the population. Single point estimate can also be biased despite the sample being selected randomly. Thus, a point estimate is often unreliable. A confidence interval is needed to reduce this unreliability.
A confidence interval for the mean is a range of values that provides an estimate of the population mean. As the...
8.7K
Strategies for Assessing and Addressing Confounding01:25

Strategies for Assessing and Addressing Confounding

365
Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
365
Estimating Population Standard Deviation01:26

Estimating Population Standard Deviation

3.3K
When the population standard deviation is unknown and the sample size is large, the sample standard deviation s is commonly used as a point estimate of σ. However, it can sometimes under or overestimate the population standard deviation. To overcome this drawback, confidence intervals are determined to estimate population parameters and eliminate any calculation bias accurately. However, this only applies to random samples from normally distributed populations. Knowing the sample mean and...
3.3K
Estimating Population Mean with Unknown Standard Deviation01:22

Estimating Population Mean with Unknown Standard Deviation

8.8K
In practice, we rarely know the population standard deviation. In the past, when the sample size was large, this did not present a problem to statisticians. They used the sample standard deviation s as an estimate for σ and proceeded as before to calculate a confidence interval with close enough results. However, statisticians ran into problems when the sample size was small. A small sample size caused inaccuracies in the confidence interval.
William S. Gosset (1876–1937) of the...
8.8K
Estimating Population Mean with Known Standard Deviation01:16

Estimating Population Mean with Known Standard Deviation

9.6K
To construct a confidence interval for a single unknown population mean μ, where the population standard deviation is known, we need sample mean as an estimate for μ and we need the margin of error. Here, the margin of error (EBM) is called the error bound for a population mean (abbreviated EBM). The sample mean is the point estimate of the unknown population mean μ.
The confidence interval estimate will have the form as follows:
(point estimate - error bound, point estimate +...
9.6K

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

Evaluation of Emergency Medicine Pharmacist Participation in Time to Oral Anticoagulation Reversal: A Systematic Review and Meta-Analysis.

Journal of the American College of Clinical Pharmacy : JACCP·2026
Same author

Bundled Care Interventions for the Management of Intracerebral Hemorrhage: A Review.

Critical care nurse·2026
Same author

Shortcomings of deep learning for distributional predictors: a note.

Biostatistics (Oxford, England)·2026
Same author

Identification and estimation of mediational effects of longitudinal modified treatment policies.

Biostatistics (Oxford, England)·2025
Same author

Relation of wind direction and coal terminal activity patterns with air pollution burden in a community bordering a coal export terminal, Curtis Bay, Maryland, USA.

Air quality, atmosphere, & health·2025
Same author

Incorrect statistical reasoning in Guyll et al. leads to biased claims about strength of forensic evidence.

Proceedings of the National Academy of Sciences of the United States of America·2024

相关实验视频

Updated: Jan 18, 2026

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

16.2K

在空间混下,共同的空间估计器的一致性.

Brian Gilbert1, Elizabeth L Ogburn1, Abhirup Datta1

  • 1Department of Biostatistics, Johns Hopkins University, 605 N Wolfe Street, Baltimore, Maryland 21215, U.S.A.

Biometrika
|September 8, 2025
PubMed
概括

空间混可能会影响回归结果. 这项研究表明,在空间混下,即使具有复杂的错误结构,一般最小平方 (GLS) 估计器也是一致的,前提是暴露具有非空间变化.

科学领域:

  • 空间统计的空间统计.
  • 地质统计学 在地质统计学
  • 计量经济学 计量经济学

背景情况:

  • 空间混,一个影响暴露和结果的未测量变量,对回归分析提出了挑战.
  • 传统的空间回归估计器在空间混下可能会表现出非对称偏差.

研究的目的:

  • 在空间混下评估空间回归估计器的非对称性能.
  • 建立在存在空间混杂的情况下对线性暴露效应的一致估计的条件.

主要方法:

  • 常规最小平方 (OLS) 和受限空间回归估计器的非对称分析.
  • 填充一致性证明一般化最小方程 (GLS) 与Matérn或平方指数内核.
  • 在固定函数和随机函数混下对空间估计器的理论分析.

主要成果:

  • 在空间混下,OLS和受限制的空间回归估计器在空间混下是异面偏差的.
  • GLS估计器在轻微假设的空间混下显示了充填一致性.
  • 空间估计器 (GLS,高斯过程,spline) 在固定和随机函数混下都是一致的.

结论:

  • 与一些文献相反,传统的空间估计器可以在空间混下一致估计线性暴露效应,如果暴露具有非空间变化.
关键词:
因果推理的原因推理.斯过程是高斯过程.一般化最小平方.空间的混 空间的混空间统计的空间统计.

更多相关视频

The Spatial Memory Game: Testing the Relationship Between Spatial Language, Object Knowledge, and Spatial Cognition
05:15

The Spatial Memory Game: Testing the Relationship Between Spatial Language, Object Knowledge, and Spatial Cognition

Published on: February 19, 2018

11.3K
Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
08:45

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

15.2K

相关实验视频

Last Updated: Jan 18, 2026

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

16.2K
The Spatial Memory Game: Testing the Relationship Between Spatial Language, Object Knowledge, and Spatial Cognition
05:15

The Spatial Memory Game: Testing the Relationship Between Spatial Language, Object Knowledge, and Spatial Cognition

Published on: February 19, 2018

11.3K
Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
08:45

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

15.2K
  • 这些发现为在空间回归与混中使用GLS和相关模型提供了理论支持.