相关实验视频
Updated: Jun 15, 2025

07:11
Sampling Soils in a Heterogeneous Research Plot
Published on: January 7, 2019
34.4K
样本大小规划,以精确和可靠地估计全球获胜概率.
1Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA; Clinical Futures, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
Contemporary clinical trials
|August 23, 2024
概括
本研究引入了一种新的样本大小公式,用于评估使用全球胜利概率 (WinP) 评估多种疾病方面的临床试验. 该公式确保了所需的精度和干预效应的保证,有助于试验设计.
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
- 医学研究 医学研究
背景情况:
- 随机对照试验 (RCT) 经常使用多个终点来全面评估干预措施.
- 估计各种疾病方面的整体治疗效果对于准确的评估至关重要.
研究的目的:
- 在具有多个终点的RCT中提出一个封闭形式的样本大小公式,用于全球获胜概率 (WinP).
- 将预先规定的精度和保证纳入全球WinP的样本大小计算中.
- 提供一种能够解释治疗组之间的不平等差异的方法.
主要方法:
- 该研究将全球WinP定义为个别终点WinP的平均值,代表治疗参与者优于对照参与者的概率.
- 它利用了WinP与接收器运行特征曲线 (AUC) 下的面积之间的等价值.
- 一个样本大小公式是根据用于比较两个AUC的方法进行调整的,允许不平等的差异.
主要成果:
- 拟议的封闭式样本大小公式有效估计了全球获胜概率.
- 模拟结果表明,该方法在实践中表现良好.
- 该公式用帕金森病临床试验设计中的实用例子来说明.
结论:
- 开发的样本大小公式提供了一个精确可靠的方法,用于规划使用全球WinP的多个终点的RCT.
- 这种方法提高了评估跨多种疾病结果的干预措施的统计学严谨性.
- 该方法适用于各种治疗领域,包括神经系统疾病,如帕金森病.
相关概念视频
Sample Size Calculation
3.2K
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...
The sample size for the given experiment or sampling effort is fundamental to any study design. Sample size decides the number of...
3.2K
Testing a Claim about Population Proportion
3.3K
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...
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...
3.3K
Sample Proportion and Population Proportion
5.2K
Collecting samples or responses from an entire population takes significant time and effort, so a researcher collects responses from only a sample of that population. Suppose a study needs to collect information about a specific mobile application. After sample collection, the researcher analyzes the data and discovers that most individuals in the sample use that specific mobile application. The sample proportion measures the number of individuals in a sample who either use or don't use the...
5.2K
Contaminants and Errors
85
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...
Another key consideration is determining the appropriate number of samples required to...
85
Estimating Population Mean with Known Standard Deviation
8.3K
To construct a confidence interval for a single unknown population mean μ, where the population standard deviation is known, we need sample mean as an estimate for μ and we need the margin of error. Here, the margin of error (EBM) is called the error bound for a population mean (abbreviated EBM). The sample mean is the point estimate of the unknown population mean μ.
The confidence interval estimate will have the form as follows:
(point estimate - error bound, point estimate +...
The confidence interval estimate will have the form as follows:
(point estimate - error bound, point estimate +...
8.3K
Margin of Error
4.0K
The margin of error is also called the maximum error of an estimate. The margin of error is the maximum possible or expected difference between the observed sample parameter value and the actual population parameter value. For proportion, it is the maximum difference between the value of sample proportion obtained from the data and the true value of population proportion. As the true value of the population parameter is not known, the margin of error is calculated using the sample statistic.
4.0K

