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

Factorial Design02:01

Factorial Design

13.0K
Factorial Analysis is an experimental design that applies Analysis of Variance (ANOVA) statistical procedures to examine a change in a dependent variable due to more than one independent variable, also known as factors. Changes in worker productivity can be reasoned, for example, to be influenced by salary and other conditions, such as skill level. One way to test this hypothesis is by categorizing salary into three levels (low, moderate, and high) and skills sets into two levels (entry level...
13.0K
Bootstrapping01:24

Bootstrapping

583
The term "bootstrap" originated in the 19th century as a metaphor for self-improvement or achieving something independently, without external assistance. This concept extends to statistical bootstrapping, a self-contained method for estimating population parameters through resampling, even though it can be computationally intensive. Developed by the American statistician Dr. Bradley Efron in 1979, bootstrapping provides a robust way to perform inference when the original sample size is...
583
Experimental Designs01:16

Experimental Designs

11.1K
An experimental design is a systematic process that allows researchers to evaluate the relationship between dependent and independent variables. There are three widely used types of experimental design - pre-experimental design, true experimental design, and quasi-experimental design. In pre-experimental design, the researcher compares the data before and after some interventions or treatments. The true-experimental design has more than one purposefully created group, a commonly measured...
11.1K
Randomized Experiments01:13

Randomized Experiments

6.7K
The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
6.7K
One-Way ANOVA: Equal Sample Sizes01:15

One-Way ANOVA: Equal Sample Sizes

3.2K
One-Way ANOVA can be performed on three or more samples with equal or unequal sample sizes. When one-way ANOVA is performed on two datasets with samples of equal sizes, it can be easily observed that the computed F statistic is highly sensitive to the sample mean.
Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...
3.2K
One-Way ANOVA: Unequal Sample Sizes01:15

One-Way ANOVA: Unequal Sample Sizes

5.7K
One-way ANOVA can be performed on three or more samples of unequal sizes. However, calculations get complicated when sample sizes are not always the same. So, while performing ANOVA with unequal samples size, the following equation is used:
5.7K

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

Permutation Tests Based on the Copula-Graphic Estimator and Their Use for Survival Tree Construction.

Statistics in medicine·2026
Same author

Multiple Contrast Tests for Count Data: Small Sample Approximations and Their Limitations.

Biometrical journal. Biometrische Zeitschrift·2025
Same author

A New Approach to the Nonparametric Behrens-Fisher Problem With Compatible Confidence Intervals.

Biometrical journal. Biometrische Zeitschrift·2025
Same author

A CD22-specific T-cell receptor enables effective adoptive T-cell therapy for B-cell malignancies.

Blood·2025
Same author

Development of intersectoral medical care for patients with 'chronic critical illness': protocol for a telemedicine interventional study with a pre-post design in out-of-hospital intensive care facilities (E=MC²).

BMJ open·2025
Same author

Three-Year Outcomes of Catheter Ablation in Patients With End-Stage Heart Failure and Atrial Fibrillation.

Circulation·2025
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: Jun 6, 2025

Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study
20:24

Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study

Published on: January 31, 2014

16.5K

不完全观察到的重复测量的非参数因数设计:一种野生的引导方法.

Lubna Amro1, Frank Konietschke2,3, Markus Pauly1,4

  • 1Department of Statistics, TU Dortmund University, Dortmund, Germany.

Biometrical journal. Biometrische Zeitschrift
|November 23, 2024
PubMed
概括
此摘要是机器生成的。

本研究引入了新的基于非参数级别的方法来分析复杂的多变量数据,特别是当数据不完整或分类时. 这些先进的技术改善了生命科学和医学研究中的统计分析.

关键词:
缺失的值是指缺失的值.非参数的假设.顺序排列的分类数据是有序的.排名测试 排名测试 排名测试反复采取措施反复采取措施.野生的启动链.

更多相关视频

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.3K
Drosophila Courtship Conditioning As a Measure of Learning and Memory
09:29

Drosophila Courtship Conditioning As a Measure of Learning and Memory

Published on: June 5, 2017

18.2K

相关实验视频

Last Updated: Jun 6, 2025

Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study
20:24

Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study

Published on: January 31, 2014

16.5K
Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.3K
Drosophila Courtship Conditioning As a Measure of Learning and Memory
09:29

Drosophila Courtship Conditioning As a Measure of Learning and Memory

Published on: June 5, 2017

18.2K

科学领域:

  • 统计 统计 统计 统计
  • 生物统计学 生物统计学
  • 生命科学 生命科学

背景情况:

  • 在生命科学中的多变量数据分析通常使用MANOVA或混合模型.
  • 这些方法需要完整的数据和特定的分布假设 (例如,连续性,共变量结构).
  • 离散或有序的分类数据对传统的参数方法构成挑战.

研究的目的:

  • 制定统计学上合理的程序来分析具有缺失值的多变量数据.
  • 扩展基于等级的方法来处理顺序或有序的分类数据.
  • 解决现有方法关于完整数据和分布假设的局限性.

主要方法:

  • 使用非参数级别的基于等级的方法.
  • 应用了一个野生启动程序.
  • 用于分析的二次形式类型测试统计数据.

主要成果:

  • 开发了不对称正确的程序来处理缺失的数据和单一的协差矩阵.
  • 证明了对顺序和有序分类数据的应用性.
  • 通过包括小样本在内的广泛模拟研究验证了程序性能.

结论:

  • 新方法为生命科学研究中的复杂数据结构提供了强大的替代方案.
  • 野生引导和基于排名的统计数据为不完整和分类的多变量数据提供了可靠的分析.
  • 这些程序在现实世界的数据示例中被验证为实际使用.