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

Interpretation of Confidence Intervals01:19

Interpretation of Confidence Intervals

5.7K
A confidence interval is a better estimate of the population than a point estimate, as it uses a range of values from a sample instead of a single value.
Confidence intervals have confidence coefficients that are crucial for their interpretation. The most common confidence coefficients are 0.90, 0.95, and 0.99, which can be written as percentages–90%, 95%, and 99%, respectively.
Suppose a person calculates a confidence interval with a confidence coefficient of 0.95. In that case, they can...
5.7K
Uncertainty: Confidence Intervals00:54

Uncertainty: Confidence Intervals

4.1K
The confidence interval is the range of values around the mean that contains the true mean. It is expressed as a probability percentage. The interpretation of a 95% confidence interval, for instance, is that the statistician is 95% confident that the true mean falls within the interval. The upper and lower limits of this range are known as confidence limits. The confidence limits for the true mean are estimated from the sample's mean, the standard deviation, and the statistical factor...
4.1K
Confidence Intervals01:21

Confidence Intervals

6.2K
An unbiased point estimate is often insufficient to predict a population estimate, such as population mean or population proportion. In this scenario, a confidence interval is used. A confidence interval is an estimate similar to a  sample proportion. However, unlike the point estimate which is a single value, the confidence interval  contains a range of values. These values have lower and upper limits, known as confidence limits, and can be designated as L1 and L2, respectively.
A...
6.2K
Confidence Coefficient01:24

Confidence Coefficient

7.6K
The confidence coefficient is also known as the confidence level or degree of confidence. It is the percent expression for the probability, 1-α, that the confidence interval contains the true population parameter assuming that the confidence interval is obtained after sufficient unbiased sampling; for example, if the CL = 90%, then in 90 out of 100 samples the interval estimate will enclose the true population parameter. Here α is the area under the curve, distributed equally under...
7.6K
Confidence Interval for Estimating Population Mean01:25

Confidence Interval for Estimating Population Mean

7.3K
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...
7.3K
Estimating Population Mean with Unknown Standard Deviation01:22

Estimating Population Mean with Unknown Standard Deviation

7.7K
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...
7.7K

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

An ecological text message experiment of Hispanic and Latino adolescents' recognition of and emotional responses to digital dating abuse behaviors.

Journal of research on adolescence : the official journal of the Society for Research on Adolescence·2026
Same author

Questionable research practices and cumulative science: The consequences of selective reporting on effect size bias and heterogeneity.

Psychological methods·2023
Same author

Validity and reliability of the Body-Esteem Scale among a diverse sample of preadolescent youth.

Psychological assessment·2023
Same author

Appropriately estimating the standardized average treatment effect with missing data: A simulation and primer.

Behavior research methods·2022
Same author

Sample size planning for replication studies: The devil is in the design.

Psychological methods·2022
Same author

Multiplicity in multiple regression: Defining the issue, evaluating solutions, and integrating perspectives.

Psychological methods·2022
Same journal

Bayesian Machine Learning Tools for Alcohol Use Disorder Research: The bpaup R Package.

Multivariate behavioral research·2026
Same journal

A Unified Framework for Jointly modelling Response Times and Item Position Effects in Computer-Based Learning Assessments.

Multivariate behavioral research·2026
Same journal

Generalizability Theory Applied to Daily Relationship Quality: Substantive and Statistical Directions.

Multivariate behavioral research·2026
Same journal

A Modularized Higher-Order Diagnostic Classification Model for Clustered Attribute Hierarchies.

Multivariate behavioral research·2026
Same journal

Generalizing Causal Effects to a Target Population Without Individual-Level Data from the Target Population.

Multivariate behavioral research·2026
Same journal

betaselectr: Selective (and Proper) Standardization in Structural Equation Models.

Multivariate behavioral research·2026
查看所有相关文章

相关实验视频

Updated: Jun 29, 2025

Assessment and Communication for People with Disorders of Consciousness
07:37

Assessment and Communication for People with Disorders of Consciousness

Published on: August 1, 2017

9.1K

标准化回归系数之间的差异的置信区间.

Samantha F Anderson1

  • 1Department of Psychology, Arizona State University, Tempe, AZ, USA.

Multivariate behavioral research
|April 1, 2024
PubMed
概括
此摘要是机器生成的。

本研究引入了用于比较标准化回归系数的正式置信区间,为非正式方法提供了更严格的替代方案. 新方法在进行统计分析的模拟中显示出卓越的性能.

关键词:
标准化回归系数标准化回归系数在信任间隔的信任间隔.多重回归的多重回归方法

更多相关视频

An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

2.1K
Evaluation of a Point-of-Care Testing Analyzer for Measuring Peripheral Blood Leukocytes
05:58

Evaluation of a Point-of-Care Testing Analyzer for Measuring Peripheral Blood Leukocytes

Published on: March 22, 2022

4.0K

相关实验视频

Last Updated: Jun 29, 2025

Assessment and Communication for People with Disorders of Consciousness
07:37

Assessment and Communication for People with Disorders of Consciousness

Published on: August 1, 2017

9.1K
An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

2.1K
Evaluation of a Point-of-Care Testing Analyzer for Measuring Peripheral Blood Leukocytes
05:58

Evaluation of a Point-of-Care Testing Analyzer for Measuring Peripheral Blood Leukocytes

Published on: March 22, 2022

4.0K

科学领域:

  • 统计 统计 统计 统计
  • 量化心理学 量化心理学
  • 计量经济学 计量经济学

背景情况:

  • 标准化回归斜率的非正式比较很常见,但缺乏统计学上的严谨性.
  • 正式的基于间隔的方法提供了更可靠的预测重要性比较.

研究的目的:

  • 引入和评估基于三角形方法的两个标准化回归系数之间的差异的置信区间.
  • 为研究人员提供一个正式的工具来比较标准化回归系数.

主要方法:

  • 使用蒙特卡洛模拟研究来评估建议的置信区间.
  • 基于覆盖率,间隔宽度,I型错误率和统计能力来评估性能.
  • 使用标准协差矩阵的替代方法与拟议的方法进行了比较.

主要成果:

  • 建议的基于三角形方法的置信区间与替代方法相比显示出更高的性能.
  • 模拟评估了软件实现,小样本性能和多重比较程序.
  • 该方法在各种条件下表现良好,包括有限的样本大小.

结论:

  • 建议的置信区间为研究人员比较标准化回归系数提供了一个有价值的,正式的工具.
  • 这种方法是对现有的分析技术的补充,而不是替代.
  • 提供了关于样本大小规划的指导和R函数,以促进实际应用.