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

Ordinal Level of Measurement00:55

Ordinal Level of Measurement

23.6K
The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
Data measured using an ordinal scale are similar to nominal scale data, but there is one major difference. The ordinal scale data can be ordered. An example of ordinal scale data is a list of the top five national parks...
23.6K
Ranks01:02

Ranks

236
Unlike parametric methods, nonparametric statistics are ideal for nominal and ordinal data, requiring fewer assumptions about the population's nature or distribution. This makes nonparametric methods easier to apply and interpret, as they do not depend on parameters like mean or standard deviation. One common approach in nonparametric analysis is to sort data according to a specific criterion. For instance, we might arrange weather data from hottest to coldest days in a month or rank cities...
236
Nominal Level of Measurement00:56

Nominal Level of Measurement

28.4K
The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. Not every statistical operation can be used with every set of data. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
The data that cannot be measured but can be grouped into categories fall under the nominal level of measurement. Data that is measured using a nominal...
28.4K
Friedman Two-way Analysis of Variance by Ranks01:21

Friedman Two-way Analysis of Variance by Ranks

189
Friedman's Two-Way Analysis of Variance by Ranks is a nonparametric test designed to identify differences across multiple test attempts when traditional assumptions of normality and equal variances do not apply. Unlike conventional ANOVA, which requires normally distributed data with equal variances, Friedman's test is ideal for ordinal or non-normally distributed data, making it particularly useful for analyzing dependent samples, such as matched subjects over time or repeated measures...
189
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

38
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
38
Compartment Models: Two-Compartment Model01:20

Compartment Models: Two-Compartment Model

5.5K
The two-compartment model divides the body into central and peripheral compartments to account for varying blood perfusion rates among organs and tissues, affecting drug distribution. The central compartment includes blood and highly perfused tissues with rapid drug distribution, while the peripheral compartment contains tissues with slower drug distribution. After a single IV bolus dose, the drug concentration is high in plasma and low in tissues. The drug distribution between compartments...
5.5K

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

Pathologic Response and Outcomes After Neoadjuvant Chemotherapy in Gastric Cancer: A NCDB Analysis.

Journal of surgical oncology·2026
Same author

Measurement of muscle passive stiffness in vibration-exposed groundskeepers.

International archives of occupational and environmental health·2026
Same author

BCGLMs: Bayesian modeling for disease prediction using compositional microbiome features.

Bioinformatics advances·2026
Same author

Persistent poverty, glycemic control and adverse COVID-19 outcomes: a retrospective study using real-world data.

BMC public health·2025
Same author

Handling rescue therapy in myasthenia gravis clinical trials: why it matters and why you should care.

Annals of clinical and translational neurology·2025
Same author

Altered Bacteria Abundance Is Associated With Outcomes in Head and Neck Squamous Cell Carcinoma.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery·2025
Same journal

Asymptotic online FWER control for dependent test statistics.

Statistical methods in medical research·2026
Same journal

Regression analysis of misclassified current status data with potentially unknown test accuracy.

Statistical methods in medical research·2026
Same journal

Bayesian multivariate linear mixed-effects models with varied association structures.

Statistical methods in medical research·2026
Same journal

Inference about the ratio of age-standardized rates between two overlapping populations.

Statistical methods in medical research·2026
Same journal

A robust neural network with random effects for subject-specific prediction of clustered count data.

Statistical methods in medical research·2026
Same journal

A comparison of methods for designing hybrid type 2 cluster-randomized trials with continuous effectiveness and implementation endpoints.

Statistical methods in medical research·2026
查看所有相关文章

相关实验视频

Updated: Jun 28, 2025

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

2.5K

对于顺序响应的贝叶斯组成模型.

Li Zhang1, Xinyan Zhang2, Justin M Leach1

  • 1Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, USA.

Statistical methods in medical research
|April 23, 2024
PubMed
概括
此摘要是机器生成的。

这项研究引入了贝叶斯组合模型的顺序响应分析组合数据,超越现有的方法在参数估计和预测微生物组和医学研究.

关键词:
组合数据是指组成的数据.汉密尔顿式蒙特卡洛的 蒙特卡洛的美国MCMCMCMCMCMCMCMC微生物组是一个微生物组.总和为零的限制限制.

更多相关视频

Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects
08:13

Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects

Published on: May 10, 2019

6.3K
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

相关实验视频

Last Updated: Jun 28, 2025

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

2.5K
Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects
08:13

Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects

Published on: May 10, 2019

6.3K
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

科学领域:

  • 统计 统计 统计 统计
  • 生物信息学是一种生物信息学.
  • 计算生物学 计算生物学

背景情况:

  • 顺序反应在医学和生物学中很常见.
  • 预测因素往往是组成性的 (固定的总和),就像微生物相对丰富.
  • 现有的模型无法考虑组合约束和预测器相关性.

研究的目的:

  • 提出一种新的贝叶斯方法,用组成预测器分析顺序响应.
  • 解决传统模型在处理固定和相关预测器方面的局限性.
  • 为微生物组和其他生物数据分析提供一个强大的框架.

主要方法:

  • 开发了顺序响应 (BCO) 的贝叶斯组成模型.
  • 使用一个结构化的规则化的马,先为系数.
  • 通过先前分配对系数实施了软和至零的限制.
  • 在R包中使用了哈密尔顿式蒙特卡洛算法.

主要成果:

  • 拟议的BCO方法在现有方法中表现出优越的性能.
  • 在参数估计和预测准确性方面都表现出色.
  • 在HMP2Data中成功识别了与炎症性肠病水平相关的微生物.

结论:

  • BCO 方法有效地通过组合预测器分析顺序响应.
  • 该方法为微生物组和类似的生物数据提供了更好的准确性.
  • 对于拟议的方法,可复制的代码和数据是可用的.