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

Cluster Sampling Method01:20

Cluster Sampling Method

12.0K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
12.0K
Survival Tree01:19

Survival Tree

109
Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
109
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

96
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
96
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

128
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
128
Frequency-dependent Selection01:21

Frequency-dependent Selection

22.1K
When the fitness of a trait is influenced by how common it is (i.e., its frequency) relative to different traits within a population, this is referred to as frequency-dependent selection. Frequency-dependent selection may occur between species or within a single species. This type of selection can either be positive—with more common phenotypes having higher fitness—or negative, with rarer phenotypes conferring increased fitness.
22.1K
Multicompartment Models: Overview01:14

Multicompartment Models: Overview

178
Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
178

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

From Five-Number Summary to Absolute Heterogeneity: Recent Methodological Advances in Meta-Analysis With Continuous Outcomes.

Journal of evidence-based medicine·2026
Same author

Spatially Correlated Analysis of Infectious Disease Outcomes Based on Bayesian Functional Hierarchical Models.

Statistics in medicine·2026
Same author

Partially Linear Additive Quantile Regression: Theory and Applications to Breast Cancer Patients' Survival.

Statistics in medicine·2026
Same author

The adaptive functional piecewise ordered weighted averaging method and its application to pollutant concentration analysis.

PloS one·2026
Same author

Digital assets: risks, regulations, mitigation.

Financial innovation·2026
Same author

A novel robust meta-analysis model using the <i>t</i> distribution for outlier accommodation and detection.

Research synthesis methods·2026

相关实验视频

Updated: Jul 17, 2025

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

3.4K

一个贝叶斯的多阶段空间时间依赖模型,用于空间聚类和变量选择.

Shaopei Ma1, Keming Yu2, Man-Lai Tang2

  • 1School of Statistics, University of International Business and Economics, Beijing, China.

Statistics in medicine
|August 31, 2023
PubMed
概括

这项研究引入了贝叶斯模型来分析时空健康数据,识别不同地区和时间的疾病风险因素. 该方法通过考虑协变效应的局部变化来改善推断.

关键词:
贝叶斯的等级模型是贝叶斯的等级模型.空间聚类是空间聚类.空间混的问题时间空间建模.选择变量的选择变量.

更多相关视频

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

15.7K
Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM
12:26

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM

Published on: October 11, 2016

13.4K

相关实验视频

Last Updated: Jul 17, 2025

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

3.4K
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

15.7K
Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM
12:26

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM

Published on: October 11, 2016

13.4K

科学领域:

  • 流行病学 流行病学
  • 生物统计学 生物统计学
  • 地理空间分析是什么

背景情况:

  • 时空流行病学分析需要识别显著的共变量及其随时间变化的影响.
  • 数据异质性意味着重要的共变量及其时间趋势在本地可能有所不同.
  • 现有的空间模型往往忽略了局部变化,导致不准确的推断.

研究的目的:

  • 为时空分析提出一个灵活的贝叶斯层次模型.
  • 同时识别具有共同时间趋势的回归系数的空间集群.
  • 选择每个空间组的显著共变量,并估计空间时间变化的疾病风险.

主要方法:

  • 开发了一种贝叶斯等级模型,用于共变量选择的二进制输入参数.
  • 采用多阶段策略来减轻来自空间结构随机组件的混偏差.
  • 通过模拟研究验证了该方法,并将其应用于低出生体重和循环系统疾病数据.

主要成果:

  • 拟议的模型有效地识别了空间集群和具有局部变化的时间效应的显著共变量.
  • 与替代方法相比,模拟研究显示出更高的性能.
  • 案例研究表明,该模型能够在特定地区和时间范围内探索疾病风险和相关因素.

结论:

  • 灵活的贝叶斯模型准确地捕捉了疾病风险和共同变量效应的时空变化.
  • 这种方法通过解决局部数据异质性来增强流行病学推断.
  • 该方法为公共卫生研究和政策提供了宝贵的见解.