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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...
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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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Clinical Trials01:16

Clinical Trials

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Clinical trials are prospective experimental studies conducted on humans to determine the safety and efficacy of treatments, drugs, diet methods, and medical devices. Using statistics in clinical trials enables researchers to derive reasonable and accurate conclusions from the collected data, allowing them to make wise decisions in uncertain situations. In medical research, statistical methods are crucial for preventing errors and bias.
There are four phases in a clinical trial. A phase one...
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Sampling Plans01:23

Sampling Plans

214
Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
214
Hazard Ratio01:12

Hazard Ratio

163
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...
163
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,...
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相关实验视频

Updated: Jul 23, 2025

A Clinical Trial Assessing the Safety, Efficacy, and Delivery of Olive-Oil-Based Three-Chamber Bags for Parenteral Nutrition
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集群随机试验中的信息性集群大小:来自TRIGGER试验的案例研究.

Brennan C Kahan1, Fan Li2, Bryan Blette3

  • 1MRC Clinical Trials Unit at UCL, London, UK.

Clinical trials (London, England)
|July 13, 2023
PubMed
概括

集群随机试验可能会产生偏差的结果,如果集群大小影响结果. 独立性估计方程为参与者平均值和集群平均值治疗效应提供了公正的估计,当集群大小具有信息性时.

关键词:
集群随机化试验是指集群随机化试验.集群平均处理效应的处理效应.估计和估计和估计.有关信息的集群大小.参与者-平均治疗效果

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科学领域:

  • 生物统计学 生物统计学
  • 临床试验 临床试验
  • 流行病学 流行病学

背景情况:

  • 集群随机试验 (CRT) 可以估计不同的参与者平均和集群平均治疗效应.
  • 当集群大小具有信息性时,这些效应可能会分歧,可能会导致标准估计者的偏见.
  • 关于CRT中信息集群大小的流行情况的经验研究很少.

研究的目的:

  • 通过重新分析红细胞输血值的试验,实证地调查CRT中的信息集群大小.
  • 为了比较参与者平均值和集群平均值的治疗效果估计.
  • 在潜在的信息集群大小下评估不同统计方法的性能.

主要方法:

  • 重新分析CRT,比较急性上部胃肠道出血的输血值.
  • 使用独立性估计方程 (在信息集群大小下不受偏见) 估计参与者平均效应.
  • 与集群平均效应估计器 (加权独立性估计方程,未加权集群级总结) 和可交换相关性的混合效应模型/GEE进行比较.

主要成果:

  • 对参与者和集群平均效应的估计差异为29%的结果>10%.
  • 在独立性估计方程和混合效应模型/GEE之间观察到显著的差异.
  • 具体的例子包括EQ-5D VAS分数和血栓栓塞/缺血事件,突出显示潜在的偏差.

结论:

  • 由于信息集群大小,CRT中的估计值可能会有所不同,因此需要仔细选择方法.
  • 独立性估计方程和加权集群层次摘要在信息集群大小合理时是首选的.
  • 适当的统计方法可确保在CRT中对治疗效应进行公正的估计.