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相关概念视频

Cluster Sampling Method01:20

Cluster Sampling Method

11.9K
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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Sample Size Calculation01:19

Sample Size Calculation

3.3K
Knowledge of the sample size is the first requirement to conduct random sampling or an experiment. The sample size is the total number of units, observations, or groups (in some cases) used to get the data to estimate a population parameter. As the name suggests, the sample size is that of the sample drawn from the population and differs from the population size.
The sample size for the given experiment or sampling effort is fundamental to any study design. Sample size decides the number of...
3.3K
Sampling Plans01:23

Sampling Plans

181
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...
181
Randomized Experiments01:13

Randomized Experiments

6.9K
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...
6.9K
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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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,...
126

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相关实验视频

Updated: Jul 1, 2025

A Clinical Trial Assessing the Safety, Efficacy, and Delivery of Olive-Oil-Based Three-Chamber Bags for Parenteral Nutrition
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对于集群随机试验的样本大小计算的实际考虑.

Clémence Leyrat1, Sandra Eldridge2, Monica Taljaard3

  • 1Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK.

Journal of epidemiology and population health
|March 13, 2024
PubMed
概括
此摘要是机器生成的。

集群随机试验 (CRT) 由于集群内相关性,需要仔细计算样本大小. 本文详细介绍了CRT的方法,包括各种设计的扩展,以确保足够的统计能力.

关键词:
集群交叉试验 集群交叉试验集群随机试验的随机试验.设计效应设计效应集群内部相关性相关性样本大小计算 样本大小计算阶梯试验的试验.

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科学领域:

  • 公共卫生 公共卫生
  • 医学研究 医学研究
  • 生物统计学 生物统计学

背景情况:

  • 当个人随机化不切实际时,集群随机试验 (CRT) 是至关重要的.
  • 集群内相关性降低了统计能力,需要调整样本大小计算.
  • 集群内部相关系数 (ICC) 量化了这种相关性.

研究的目的:

  • 为平行臂CRT概述样本大小计算原则.
  • 将这些原则扩展到具有交叉,基线测量和阶梯设计的CRT.
  • 为估计ICC提供指导,并在CRT中解决实际考虑.

主要方法:

  • 对各种CRT设计的样本大小计算原理的描述.
  • 解释如何在不同的CRT结构中扩展计算.
  • 讨论估计ICC和处理消耗,小集群数量和共变量的方法.

主要成果:

  • 为各种CRT设计中的样本大小计算提供了一个框架.
  • 为选择适当的ICC估计提供指导.
  • 突出了强大的CRT规划和分析的关键考虑因素.

结论:

  • 精确的样本大小计算对于CRT的有效性和功率至关重要.
  • 讨论的方法适用于一系列复杂的集群随机试验设计.
  • 研究人员在实践方面得到指导,以提高CRT的可靠性.