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相关概念视频

Sampling Plans01:23

Sampling Plans

165
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...
165
Sampling Distribution01:12

Sampling Distribution

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Given simple random samples of size n from a given population with a measured characteristic such as mean, proportion, or standard deviation for each sample, the probability distribution of all the measured characteristics is called a sampling distribution. How much the statistic varies from one sample to another is known as the sampling variability of a statistic. You typically measure the sampling variability of a statistic by its standard error. The standard error of the mean is an example...
12.3K
Stratified Sampling Method01:16

Stratified Sampling Method

11.7K
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. 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.
To choose a stratified sample, divide the population into groups called strata and then take a...
11.7K
Contaminants and Errors01:16

Contaminants and Errors

83
Effective sample preparation is crucial for accurate and reliable laboratory analysis. During this process, two significant sources of error can arise: concentration bias from improper sample splitting and contamination caused by methods used to reduce particle size, such as grinding or homogenization. Identifying and minimizing these potential errors is crucial to ensuring the validity of the analysis.
Another key consideration is determining the appropriate number of samples required to...
83
Choosing Between z and t Distribution01:25

Choosing Between z and t Distribution

2.7K
The z and the Student t distribution estimate the population mean using the sample mean and standard deviation. However, to decide which distribution to use for a calculation, one needs to determine the sample size, the nature of the distribution, and whether the population standard deviation is known. If the population standard deviation is known and the population is normally distributed, or if the sample size is greater than 30, the z distribution is preferred. The Student t distribution is...
2.7K
Sampling Methods: Overview01:06

Sampling Methods: Overview

272
A sample refers to a smaller subset representative of a larger population. In analytical chemistry, studying or analyzing an entire population is often impractical or impossible. Therefore, samples are used to draw inferences and generalize the whole population. The sampling method selects individuals or items from a population to create a sample. Standard sampling methods include random, judgemental, systematic, stratified, and cluster sampling. 
In analytical chemistry, the choice of...
272

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Sampling Strategies and Processing of Biobank Tissue Samples from Porcine Biomedical Models
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生物等价性设计与采样分布段

Luke Hagar1, Nathaniel T Stevens2

  • 1Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada.

Statistics in medicine
|January 24, 2025
PubMed
概括
此摘要是机器生成的。

本研究引入了一种更快的仿真方法,用于生物等效功率分析,为临床试验设计提供准确的样本大小建议. 该方法有效地近似功率曲线,而不需要完全估计分布.

关键词:
这就是Sobol'序列.韦尔奇的t-试验平均生物等价性的平均值.动力分析分析能力分析可扩展的设计可扩展的设计.

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科学领域:

  • 生物统计学 生物统计学
  • 临床试验设计 临床试验设计
  • 药理动力学 药理动力学

背景情况:

  • 功率分析在生物等价性研究中至关重要,以确定检测临床显著差异所需的样本大小.
  • 传统方法往往依赖于耗时的计算机模拟来近似复杂的测试统计的采样分布.
  • 精确的功率计算确保了有效和道德的临床试验进行.

研究的目的:

  • 开发一种新的,高效的基于模拟的方法,用于在生物等价性测试中近似计算功率曲线.
  • 通过探索样本分布的相关部分,使得无偏见的样本大小推成为可能.
  • 证明该方法适用于具有不平等差异的两组生物等价性试验及其在更广泛的临床设计中的潜力.

主要方法:

  • 提出一种新的基于模拟的方法,通过选择性地探索采样分布,有效地近似功率曲线.
  • 该方法避免估计整个采样分布,减少计算时间.
  • 在R中使用"dent"包用于两组具有不平等差异的生物等价性测试来证明实施.

主要成果:

  • 拟议的方法提供了一种计算效率高的方法,用于生物等价性测试的近似功率曲线.
  • 尽管没有估计完整的抽样分布,但该方法产生了公正的样本大小建议.
  • 该方法用于两组具有不平等差异的生物等价性,说明了该方法的实际实用性.

结论:

  • 一种新的,高效的模拟技术加速了生物等价性研究中的功率曲线近似.
  • 该方法可为临床试验规划提供准确和公正的样本大小确定.
  • 开发的方法和R包 ("dent") 在临床研究设计中提供了更广泛的适用性.