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

Decision Making: P-value Method01:09

Decision Making: P-value Method

5.4K
The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim  is also stated. These statements can act as null and alternative hypotheses:  a null hypothesis would be a neutral statement while the alternative hypothesis can...
5.4K
Bonferroni Test01:10

Bonferroni Test

2.7K
The Bonferroni test is a statistical test named after Carlo Emilio Bonferroni, an Italian mathematician best known for Bonferroni inequalities. This statistical test is a type of multiple comparison test to determine which means are different than the rest. Bonferroni test can minimize the Type 1 error by reducing the significance level alpha, which otherwise increases with sample pairs.
The means of different samples are first paired in all possible combinations.
The null hypothesis of the...
2.7K
P-value01:10

P-value

6.9K
P-value is one of the most crucial concepts in statistics.
P-value stands for the probability value.  P-value is the probability that, if the null hypothesis is true, the results from another randomly selected sample will be as extreme or more extreme as the results obtained from the given sample.
A large P-value calculated from the data indicates to  not reject the null hypothesis. But a higher P-value does not mean that the null hypothesis is true. The smaller the P-value, the more...
6.9K
Wald-Wolfowitz Runs Test II01:17

Wald-Wolfowitz Runs Test II

251
The Wald-Wolfowitz runs test, commonly referred to as the runs test, is a nonparametric test used to assess the randomness of ordered data. The test evaluates the number of runs, which are consecutive sequences of similar elements within the data. If the number of runs is significantly higher or lower than expected, the data is considered non-random, indicating a detectable pattern or structure.
For binary data, runs are identified using symbols such as + and −, or equivalently, 1s and...
251
Decision Making: Traditional Method01:14

Decision Making: Traditional Method

4.0K
The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
4.0K
Testing a Claim about Population Proportion01:24

Testing a Claim about Population Proportion

3.3K
A complete procedure for testing a claim about a population proportion is provided here.
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...
3.3K

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

Editorial for the Special Collection "MCP 2022".

Biometrical journal. Biometrische Zeitschrift·2025
Same author

Multiple multi-sample testing under arbitrary covariance dependency.

Statistics in medicine·2023
Same author

Long-term temporal evolution of extreme temperature in a warming Earth.

PloS one·2023
Same author

Multiple two-sample testing under arbitrary covariance dependency with an application in imaging mass spectrometry.

Biometrical journal. Biometrische Zeitschrift·2022
Same author

Special issue on multiple comparisons (MCP 2019).

Biometrical journal. Biometrische Zeitschrift·2022
Same author

Obstructive sleep apnea syndrome as a rare presentation in a young girl with a central nervous system tumor.

Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine·2021
Same journal

Ensuring Quality in Preclinical Research: The Importance of Being Human.

Biometrical journal. Biometrische Zeitschrift·2026
Same journal

Addressing Cluster-Level Treatment Effect Heterogeneity in Sample Size Determination for Hierarchical 2 × 2 Factorial Designs.

Biometrical journal. Biometrische Zeitschrift·2026
Same journal

A Multiple Imputation Approach to Distinguish Curative From Life-Prolonging Effects in the Presence of Missing Covariates.

Biometrical journal. Biometrische Zeitschrift·2026
Same journal

Tests for Categorical Data Beyond Pearson: A Distance Covariance and Energy Distance Approach.

Biometrical journal. Biometrische Zeitschrift·2026
Same journal

Nonparametric Estimation of the Patient-Weighted While-Alive Estimand.

Biometrical journal. Biometrische Zeitschrift·2026
Same journal

Two-Stage Multiple Test Procedures Controlling False Discovery Rate With Auxiliary Variable and Their Application to Set4 <math><semantics><mi>Δ</mi> <annotation>$\Delta$</annotation></semantics></math> Mutant Data.

Biometrical journal. Biometrische Zeitschrift·2026
查看所有相关文章

相关实验视频

Updated: Jul 12, 2025

Combined Immunofluorescence and DNA FISH on 3D-preserved Interphase Nuclei to Study Changes in 3D Nuclear Organization
13:55

Combined Immunofluorescence and DNA FISH on 3D-preserved Interphase Nuclei to Study Changes in 3D Nuclear Organization

Published on: February 3, 2013

18.5K

用随机p值对离散数据进行复合零假设的多重测试.

Daniel Ochieng1, Anh-Tuan Hoang1, Thorsten Dickhaus1

  • 1Institute for Statistics, University of Bremen, Bremen, Germany.

Biometrical journal. Biometrische Zeitschrift
|October 19, 2023
PubMed
概括
此摘要是机器生成的。

随机的p值为统计测试中的保守性提供了一个解决方案,特别是在离散测试统计数据或非最小有利的参数配置的情况下. 这些新的方法在替代假设下保持有效性并提高功率.

关键词:
保守的测试是保守的测试.离散分布的测试统计数据测试组测试 测试组测试 测试组测试多重比较多次比较.随机测试是一种随机测试.

更多相关视频

How to Calculate and Validate Inter-brain Synchronization in a fNIRS Hyperscanning Study
05:33

How to Calculate and Validate Inter-brain Synchronization in a fNIRS Hyperscanning Study

Published on: September 8, 2021

6.6K
Barnes Maze Testing Strategies with Small and Large Rodent Models
12:59

Barnes Maze Testing Strategies with Small and Large Rodent Models

Published on: February 26, 2014

42.1K

相关实验视频

Last Updated: Jul 12, 2025

Combined Immunofluorescence and DNA FISH on 3D-preserved Interphase Nuclei to Study Changes in 3D Nuclear Organization
13:55

Combined Immunofluorescence and DNA FISH on 3D-preserved Interphase Nuclei to Study Changes in 3D Nuclear Organization

Published on: February 3, 2013

18.5K
How to Calculate and Validate Inter-brain Synchronization in a fNIRS Hyperscanning Study
05:33

How to Calculate and Validate Inter-brain Synchronization in a fNIRS Hyperscanning Study

Published on: September 8, 2021

6.6K
Barnes Maze Testing Strategies with Small and Large Rodent Models
12:59

Barnes Maze Testing Strategies with Small and Large Rodent Models

Published on: February 26, 2014

42.1K

科学领域:

  • 统计 统计 统计 统计
  • 假设测试 假设测试

背景情况:

  • 来自连续测试统计数据的P值在零假设下通常是统一的.
  • 在p值中的保守性源于离散测试统计数据或非最小有利参数配置 (LFCs).

研究的目的:

  • 介绍和评估使用随机p值的两种新方法.
  • 为了解决离散统计和复合无数的假设测试中的保守性.

主要方法:

  • 开发了两个随机的p值方法.
  • 在二项式和组测试模型下对复合无假设测试的应用.
  • 在指数数组内对离散统计模型的随机p值的验证.

主要成果:

  • 与非随机版本相比,在零假设下,拟议的随机p值在零假设下是不那么保守的.
  • 随机的p值在替代假设下是随机的,不是更小的,表明维持或改善的功率.
  • 在各种离散统计模型中证明随机p值的有效性.

结论:

  • 随机的p值有效地减轻了假设测试中的保守性.
  • 提出的方法是有效的,在统计能力方面具有优势.
  • 这些方法适用于复杂的统计模型和设计.