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相关概念视频

Longitudinal Research02:20

Longitudinal Research

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Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
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Sample Size Calculation01:19

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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...
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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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One-Way ANOVA: Unequal Sample Sizes01:15

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One-way ANOVA can be performed on three or more samples of unequal sizes. However, calculations get complicated when sample sizes are not always the same. So, while performing ANOVA with unequal samples size, the following equation is used:
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Updated: Jan 20, 2026

Using an Automated Hirschberg Test App to Evaluate Ocular Alignment
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在R的纵向模型的功率和样本大小 - 长功率包和闪亮的应用程序.

Samuel Iddi1, Michael C Donohue2

  • 1Department of Statistics and Actuarial Science, University of Ghana, Legon-Accra, Ghana also Data Measurement and Evaluation Unit, African Population and Health Research Center (APHRC), Nairobi, Kenya.

The R journal
|January 19, 2026
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概括
此摘要是机器生成的。

计算纵向研究的样本大小对于可靠的医学研究至关重要. 这项研究提供了公式和用户友好的应用程序,以帮助研究人员确定连续纵向数据的适当样本大小,包括阿尔茨海默氏症临床试验.

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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
  • 医学研究方法学 医学研究方法学

背景情况:

  • 纵向研究在医学研究中是必不可少的,用于跟踪随时间的变化.
  • 准确的样本大小计算对于确保这些研究具有足够的统计能力和有效的推断至关重要.
  • 在纵向研究中确定样本大小的现有方法是复杂的,并取决于各种因素.

研究的目的:

  • 审查并提出连续纵向数据的样本大小公式.
  • 为研究人员引入一个实用工具 (Shiny app) 来计算样本大小.
  • 用ADNI数据为阿尔茨海默病临床试验的样本大小估计提供便利.

主要方法:

  • 对纵向研究的样本大小计算方法的文献综述.
  • 开发用于连续纵向数据的样本大小公式.
  • 创建一个Shiny应用程序,用于交互式样本大小估计.
  • 使用阿尔茨海默病神经成像计划 (ADNI) 数据进行特定参数估计.

主要成果:

  • 提供了计算连续纵向数据样本大小的公式和示例.
  • 推出了Shiny应用程序,使研究人员能够输入试点估计,用于样本大小计算.
  • 该应用程序可以使用ADNI数据估计阿尔茨海默病研究的试点参数.
  • 可以生成样本大小和功率曲线来评估研究设计的操作特性.

结论:

  • 开发的套件和Shiny应用程序简化了对纵向研究的样本大小的确定.
  • 这些工具增强了研究人员设计强大的临床试验的能力,特别是在阿尔茨海默病方面.
  • 这些资源有助于评估研究设计效率,以获得纵向连续结果.