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

Biostatistics: Overview01:20

Biostatistics: Overview

226
Biostatistics plays a crucial role in understanding and analyzing data in healthcare and biology. Biostatisticians conduct experiments, gather evidence, and draw meaningful conclusions using statistical methods and techniques. Different variables form the foundation of biostatistical analysis, allowing researchers to understand and interpret data effectively. These variables are classified into different types, each serving a specific purpose in statistical analysis.
Discrete variables are...
226
Current Trends in Nursing II01:30

Current Trends in Nursing II

1.2K
Trends in nursing are multifactorial and associated with changes in society, within the nursing profession, and in other professions. Notably, telehealth and remote nursing contribute to successful healthcare delivery for numerous patients and help reduce stress for nurses due to nursing shortages. Nurses can reach patients, monitor their conditions, and interact with them using computers, audio, visual accessories, and telephones—for example, remote patient monitoring systems. Likewise,...
1.2K
Theoretical Foundations of Nursing Practice01:30

Theoretical Foundations of Nursing Practice

11.2K
Theories play an essential role in organizing patient care. Theories refer to a proposed or followed belief, policy, or procedure that is the basis for action. Nursing theories are knowledge-based concepts that guide nurses' actions, influence nursing education and practice, and allow nurses to care for their patients.
Theories provide a perspective to assess patients' conditions and organize data and methods. They also assist in analyzing and interpreting information. They represent a...
11.2K
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

312
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
312
Nursing Interventions II: Selecting and Classifying the Nursing Interventions01:29

Nursing Interventions II: Selecting and Classifying the Nursing Interventions

2.1K
Creating and executing a nursing diagnosis helps nurses plan care and guide patient, family, and community interventions. They are developed based on a patient's physical evaluation and support measuring the outcomes. It is not recommended to select random interventions throughout the planning process. Instead, consider the following six essential factors when choosing interventions:
2.1K
Study Design in Statistics01:15

Study Design in Statistics

7.9K
A study design is a set of techniques that allow a researcher to collect and analyze data from different variables defined for a specific research problem. Statistics is commonly for effective study design and more robust experiments,
Does aspirin reduce the risk of heart attacks? Is one brand of fertilizer more effective at growing roses than another? Is fatigue as dangerous to a driver as the influence of alcohol? Questions like these are answered using randomized experiments with proper...
7.9K

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

Evaluating Polygenic Score Transferability for Lipid Traits in Underrepresented Populations: Evidence from Samoan Cohorts.

medRxiv : the preprint server for health sciences·2026
Same author

The relationship of neighborhood socioeconomic disadvantage and pretreatment cancer-related cognitive impairment in women with breast cancer: A post hoc analysis of a randomized controlled trial.

Cancer·2026
Same author

Caregivers' Perspectives on Cancer-Related Cognitive Impairment in Older Adults With Acute Myeloid Leukemia Receiving Chemotherapy.

Oncology nursing forum·2026
Same author

Incorporating dietary information to enhance polygenic prediction models with applications to body mass index and type 2 diabetes.

Genes & nutrition·2026
Same author

Meta-analysis of over 8,000 individuals from Hawai'i and Samoa for genetic associations to cardiometabolic phenotypes.

medRxiv : the preprint server for health sciences·2026
Same author

Impact of <i>IL6</i> and <i>IL10</i> Genotype on Cytokines and Preeclampsia in a Pregnant Multi-Ethnic Cohort of Women With Overweight and Obesity.

Biological research for nursing·2026

相关实验视频

Updated: Jun 10, 2025

Basics of Multivariate Analysis in Neuroimaging Data
06:35

Basics of Multivariate Analysis in Neuroimaging Data

Published on: July 24, 2010

16.8K

护理研究中的多变量贝叶斯分析:一本入门指南

Lacey W Heinsberg1,2, Tara S Davis2, Dylan Maher1

  • 1Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA.

Biological research for nursing
|October 16, 2024
PubMed
概括
此摘要是机器生成的。

多变量贝叶斯方法使护理研究能够分析复杂的,相关的健康数据,揭示复杂的生物系统关系,以进行更好的干预. 这种方法增强了对表型的理解,并支持由护士领导的健康计划.

关键词:
在bnlearn学习.数据科学数据科学基因组学就是基因组学.这就是为什么mvBIMBAMBAM.护士科学家护士科学家俄米克斯 (omicsics) 是一个电子产品.

更多相关视频

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts
08:51

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts

Published on: September 20, 2024

1.2K
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

15.6K

相关实验视频

Last Updated: Jun 10, 2025

Basics of Multivariate Analysis in Neuroimaging Data
06:35

Basics of Multivariate Analysis in Neuroimaging Data

Published on: July 24, 2010

16.8K
Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts
08:51

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts

Published on: September 20, 2024

1.2K
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

15.6K

科学领域:

  • 护理研究 护理研究
  • 生物统计学 生物统计学
  • 遗传学 是一个遗传学.
  • 精确的健康 精确的健康

背景情况:

  • 护理研究越来越多地使用具有相关表型的大型多维数据集,这给统计学带来了挑战.
  • 传统的统计方法在遗传关联研究中与多线性和模糊的复杂关系作斗争.
  • 对复杂的生物系统的全面理解往往受到传统分析方法的限制.

研究的目的:

  • 引入多变量贝叶斯方法作为护理研究的强大工具.
  • 展示这些方法如何同时探索多个表型及其相关性.
  • 突出发现对生物系统的新见解的潜力,并为护士主导的干预提供信息.

主要方法:

  • 应用多变量贝叶斯方法来分析复杂的,相关的表型.
  • 同时探索多个现象型,考虑相关性结构.
  • 将先前的知识纳入统计模型,以获得更现实的生物系统视图.
  • 使用bnlearn和mvBIMBAM等特定软件程序进行分析.

主要成果:

  • 多变量贝叶斯式方法有助于探索表型之间的复杂关系.
  • 这些方法允许估计关联概率和直接/间接影响.
  • 该方法提供了一个更现实的看法,在生物系统内的统计关系.
  • 发现对已确立和未发现的联系的潜在新见解.

结论:

  • 多变量贝叶斯方法比传统的护理研究方法具有显著的优势.
  • 这些方法可以更好地了解表型,改善护士主导的干预和预防计划.
  • 这篇论文提供了实用工具和例子,以将这些分析扩展到护理研究问题.