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相关概念视频

Relative Risk01:12

Relative Risk

118
Relative risk (RR) is a statistical measure commonly used in epidemiology to compare the likelihood of a particular event occurring between two groups. This metric is important for evaluating the relationship between exposure to a specific risk factor and the probability of a particular outcome. It plays a crucial role in medical research, public health studies, and risk assessment. Relative risk quantifies how much more (or less) likely an event is to occur in an exposed group compared to an...
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Randomized Experiments01:13

Randomized Experiments

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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...
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Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

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Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
121
Hazard Ratio01:12

Hazard Ratio

91
The hazard ratio (HR) is a widely used measure in clinical trials to compare the risk of events, such as death or disease recurrence, between two groups over time. It reflects the ratio of hazard rates—the instantaneous risk of the event occurring—between a treatment group and a control group. This measure provides valuable insights into the relative effectiveness of a treatment by assessing how the risk of an event differs between the two groups.
For example, in a clinical trial...
91
Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

155
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
155
Odds Ratio01:09

Odds Ratio

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The odds ratio (OR) is a statistical measure used extensively in epidemiology and research to quantify the strength of association between exposure and outcome across different groups. Unlike relative risk, which compares the probabilities of an event occurring, the odds ratio compares the odds of an event occurring in the exposed group to the odds of it occurring in the unexposed group. The odds, in this context, are calculated as the probability of the event happening divided by the...
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相关实验视频

Updated: Jun 8, 2025

An R-Based Landscape Validation of a Competing Risk Model
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在一个集群随机试验中估计调整后的风险差异,并对个体水平进行分析.

Jules Antoine Pereira Macedo1, Bruno Giraudeau1,2, Escient Collaborators

  • 1Université de Tours, Université de Nantes, INSERM, SPHERE U1246, Tours, France.

Statistical methods in medical research
|November 6, 2024
PubMed
概括

在集群随机试验 (CRT) 中估计风险差异至关重要. 模拟结果表明,高斯分布与通用估计方程 (GEE) 为计算干预效应提供了强大而简单的方法.

关键词:
二元结果的二元结果.集群随机试验是指一个集群随机试验.通过g计算计算.一般化估计方程的估计方程.一般化的线性混合模型.风险差异风险差异的区别

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相关实验视频

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科学领域:

  • 生物统计学 生物统计学
  • 临床试验方法论 临床试验方法论
  • 流行病学 流行病学

背景情况:

  • 集群随机试验 (CRT) 经常报告二元结果的几率比率.
  • 康索尔特声明建议报告相对和绝对干预效应.
  • 在CRT中估计绝对干预效应,例如风险差异 (RD),需要仔细考虑方法.

研究的目的:

  • 评估在集群随机试验 (CRT) 中估计风险差异 (RD) 的方法.
  • 为了比较条件 (GLMM) 和边际 (GEE) 方法,使用高斯分布,二项式分布和波松分布.
  • 为了评估偏差,标准错误估计,I型错误和覆盖率.

主要方法:

  • 在CRTs框架内进行了一项模拟研究.
  • 方法包括通用线性混合模型 (GLMM) 和通用估计方程 (GEE).
  • 考虑的分布是高斯式,二项式和波松式,用于二项式/波松式RD估计的g计算.

主要成果:

  • 所有方法都表明风险差异估计没有偏差.
  • 在特定条件下,GEE方法经历了趋同问题 (低ICC,少数集群,小集群大小,许多共变量,低流行率).
  • 高斯分布 (两种方法) 和 GEE (二项式/Poisson) 显示出令人满意的标准误差估计;GEE在I型误差和覆盖率方面表现优于GLMM.

结论:

  • 建议使用高斯分布,因为它可以简单地估计CRT中的RD.
  • 由于I型错误和覆盖范围的性能更好,GEE方法通常比GLMM更受欢迎.
  • 当GEE遇到融合问题时,可以使用GLMM.