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相关概念视频

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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Group Design02:01

Group Design

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The most basic experimental design involves two groups: the experimental group and the control group. The two groups are designed to be the same except for one difference— experimental manipulation. The experimental group gets the experimental manipulation—that is, the treatment or variable being tested—and the control group does not. Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between...
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Random Sampling Method01:09

Random Sampling Method

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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures 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. Among the various sampling methods used by...
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Random Variables01:09

Random Variables

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A random variable is a single numerical value that indicates the outcome of a procedure. The concept of random variables is fundamental to the probability theory and was introduced by a Russian mathematician, Pafnuty Chebyshev, in the mid-nineteenth century.
Uppercase letters such as X or Y denote a random variable. Lowercase letters like x or y denote the value of a random variable. If X is a random variable, then X is written in words, and x is given as a number.
For example, let X = the...
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Wald-Wolfowitz Runs Test II01:17

Wald-Wolfowitz Runs Test II

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The Wald-Wolfowitz runs test, commonly referred to as the runs test, is a nonparametric test used to assess the randomness of ordered data. The test evaluates the number of runs, which are consecutive sequences of similar elements within the data. If the number of runs is significantly higher or lower than expected, the data is considered non-random, indicating a detectable pattern or structure.
For binary data, runs are identified using symbols such as + and −, or equivalently, 1s and...
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Sampling Plans01:23

Sampling Plans

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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...
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相关实验视频

Updated: Jun 11, 2025

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
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强迫随机化:什么,为什么,以及如何

Kerstine Carter1, Olga Kuznetsova2, Volodymyr Anisimov3

  • 1Boehringer-Ingelheim Pharmaceuticals Inc, Ridgefield, CT, USA.

BMC medical research methodology
|October 8, 2024
PubMed
概括
此摘要是机器生成的。

临床试验中的强制随机化 (FR) 通过防止药物供应问题,提高了患者的体验和效率. 精心规划和供应策略确保随机对照试验 (RCT) 中的风险和治疗不平衡最小.

关键词:
药物供应链管理 药物供应链管理交互式响应技术 (IRT) 是一种互动式响应技术.多中心临床试验多中心临床试验波森-马模型是什么?

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Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
13:04

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科学领域:

  • 临床试验设计 临床试验设计
  • 药学研究 药学研究
  • 生物统计学 生物统计学

背景情况:

  • 临床场所可能会遇到这样的情况:由于在场所无法提供治疗,因此无法随机选择符合条件的参与者.
  • 交互响应技术 (IRT) 允许"强制随机化" (FR) 将参与者分配到可用的治疗臂中.
  • 行业共识表明,如果实例有限,但统计性质需要进一步了解,则在确认性试验中可以接受FR.

研究的目的:

  • 探索随机对照试验 (RCT) 中强制随机化 (FR) 的统计特性和实际影响.
  • 在使用FR时,评估不同IRT配置和药物供应策略对试验操作的影响.
  • 为开发和评估结合FR的随机化设计提供框架.

主要方法:

  • 描述了四个具有和没有FR的IRT配置,用一个例子说明.
  • 进行了数据库搜索 (Cortellis),以确定FR在临床实践中的流行率.
  • 开发了一个用于评估FR设计的模板,并将其应用于各种招聘和供应场景下的假设多中心RCT,并使用Julia代码进行模拟.

主要成果:

  • FR可以消除患者拒绝,改善物流,药物管理,成本效益,减少招聘时间.
  • 科特利斯的搜索显示,FR的使用报告有限,通常记录在IRT规范中.
  • 模拟表明,在现实的环境中,FR的百分比较低;FR的补充和高补给减少了治疗失衡和招聘时间,而药物过量主要受到补给策略的影响.

结论:

  • 当与适当的药物供应策略相结合时,FR可显著改善患者/现场体验,试验物流和效率.
  • FR有效地防止拒绝和揭开盲目,有助于更顺利地进行审判.
  • 当正确规划和实施时,FR是多中心RCT的有价值特征.