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相关概念视频

Sample Size Calculation01:19

Sample Size Calculation

6.2K
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...
6.2K
Study Design in Statistics01:15

Study Design in Statistics

9.9K
A study design is a set of techniques that allow a researcher to collect and analyze data from different variables defined for a specific research problem. Statistics is commonly for effective study design and more robust experiments,
Does aspirin reduce the risk of heart attacks? Is one brand of fertilizer more effective at growing roses than another? Is fatigue as dangerous to a driver as the influence of alcohol? Questions like these are answered using randomized experiments with proper...
9.9K
Experimental Designs01:16

Experimental Designs

16.5K
An experimental design is a systematic process that allows researchers to evaluate the relationship between dependent and independent variables. There are three widely used types of experimental design - pre-experimental design, true experimental design, and quasi-experimental design. In pre-experimental design, the researcher compares the data before and after some interventions or treatments. The true-experimental design has more than one purposefully created group, a commonly measured...
16.5K
Testing a Claim about Population Proportion01:24

Testing a Claim about Population Proportion

3.9K
A complete procedure for testing a claim about a population proportion is provided here.
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...
3.9K
Sampling Distribution01:12

Sampling Distribution

16.5K
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...
16.5K
One-Way ANOVA: Equal Sample Sizes01:15

One-Way ANOVA: Equal Sample Sizes

4.0K
One-Way ANOVA can be performed on three or more samples with equal or unequal sample sizes. When one-way ANOVA is performed on two datasets with samples of equal sizes, it can be easily observed that the computed F statistic is highly sensitive to the sample mean.
Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...
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相关实验视频

Updated: Jan 8, 2026

Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow
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通过有效样本大小提高贝叶斯篮试验设计的可解释性.

Xin Chen1, Jingyi Zhang1, Wenyun Yang1

  • 1Department of Biostatistics, China Pharmaceutical University, Nanjing, China.

BMC medical research methodology
|December 16, 2025
PubMed
概括
此摘要是机器生成的。

有效样本大小 (ESS) 量化了贝叶斯篮试验中的信息借用,有助于设计和解释. 这种统计工具有助于研究人员了解数据如何跨瘤类型共享,以获得更好的试验结果.

关键词:
篮球试验 篮球试验贝叶斯临床试验设计 贝叶斯临床试验设计贝叶斯的等级模型是贝叶斯的等级模型.有效样本大小是有效的样本大小.信息借款信息借款

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相关实验视频

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Barnes Maze Testing Strategies with Small and Large Rodent Models
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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
  • 贝叶斯的推理是贝叶斯的推理.

背景情况:

  • 在篮子试验中,人们对贝叶斯的方法越来越感兴趣,以便在不同类型的瘤中共享信息.
  • 现有的贝叶斯层次模型 (BHM) 缺乏量化信息借贷的明确措施.
  • 非统计学家由于缺乏可解释性而难以理解复杂的贝叶斯设计.

研究的目的:

  • 引入和验证有效样本大小 (ESS) 作为在贝叶斯篮子试验中量化信息借用的工具.
  • 在临床试验的设计和分析阶段展示ESS的实用性.
  • 为复杂的贝叶斯统计模型提供更易解释的度量.

主要方法:

  • 在贝叶斯篮试验中利用有效样本大小 (ESS) 概念.
  • 提出基于ESS的信息借贷策略.
  • 使用平均平方误差 (MSE) 来推导ESS,平衡偏差和方差.
  • 重新分析RAGNAR研究并进行模拟研究以证明ESS的可解释性.

主要成果:

  • 欧洲信息系统有效量化了信息借用对平均平方误差 (MSE) 的影响.
  • ESS直观地描述了跨瘤类型的信息借款程度.
  • 欧洲统计系统证明了与I型错误率和统计能力的一致性,作为一种有价值的分析补充.

结论:

  • 使用ESS量化信息借款有助于试验人员设计贝叶斯篮子试验.
  • 通过ESS,便于对贝叶斯分析结果进行合理的评估和解释.
  • ESS支持敏感性分析,并有助于确定试验中适当的信息借款量.