Power and Sample Size for Multilevel and Longitudinal Study Designs

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Week 1: Introduction to Multilevel and Longitudinal Designs
Week 2: Foundations of Complex Multilevel and Longitudinal Designs
Week 3: Model Assumptions, Alignment, Missing Data, and Dropout
Week 4: Inputs to Analysis, Recruitment Feasibility, and Multiple Aims

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Power and Sample Size for Longitudinal and Multilevel Study Designs, a five-week, fully online course covers innovative, research-based power and sample size methods, and software for multilevel and longitudinal studies. The power and sample size methods and software taught in this course can be used for any health-related, or more generally, social science-related (e.g., educational research) application. All examples in the course videos are from real-world studies on behavioral and social science employing multilevel and longitudinal designs. The course philosophy is to focus on the conceptual knowledge to conduct power and sample size methods. The goal of the course is to teach and disseminate methods for accurate sample size choice, and ultimately, the creation of a power/sample size analysis for a relevant research study in your professional context. Power and sample size selection is one of the most important ethical questions researchers face. Interventional studies that are too large expose human volunteer research participants to possible, and needless, harm from research. Interventional studies that are too small will fail to reach their scientific objective, again bringing possible harm to research participants, without the possibility of concomitant gain from the increase in knowledge. For observational studies in which there are no possible harms to the participants, such as observational studies, proper power ensures good stewardship of both time and money. Most National Institutes of Health (NIH) study sections will only fund a grant if the grantee has written a compelling and accurate power and sample size analysis. The Institute of Education Sciences (IES), the statistics, research, and evaluation arm of the U.S. Department of Education, also offers competitive grants requiring a compelling and accurate power and sample size analysis (Goal 3: Efficacy and Replication and Goal 4: Effectiveness/Scale-Up). At the end of the online course, learners will be able to: • Use a framework and strategy for study planning • Write study aims as testable hypotheses • Describe a longitudinal and multilevel study design • Write a statistical analysis plan • Plan a sampling design for subgroups, e.g. racial and ethnic • Demonstrate the feasibility of recruitment • Describe expected missing data and dropout • Write a power and sample size analysis that is aligned with the planned statistical analysis This is a five-week intensive and interactive online course. We will use a mix of instructional videos, software demonstration videos, online discussion forums, online readings, quizzes, exercise assignments, and peer-review assignments. The final course project is a peer-reviewed research study you design for future power or sample size analysis.

多层次和纵向研究设计的功效和样本数量:纵向和多层次研究设计的功效和样本数量,为期五周的在线课程,涵盖了创新的,基于研究的功效和样本数量方法,以及用于多层次和纵向研究的软件。本课程中讲授的功效和样本量方法以及软件可用于任何与健康相关的或更普遍的与社会科学相关的应用(例如教育研究)。该课程视频中的所有示例均来自采用多层次和纵向设计的行为和社会科学的现实世界研究。该课程的理念是专注于概念知识,以进行功效和样本量方法。本课程的目的是讲授和传播用于准确选择样本量的方法,并最终为您的专业背景下的相关研究创建功效/样本量分析。 功效和样本量的选择是研究人员面临的最重要的道德问题之一。太大的干预研究使人类志愿者研究参与者容易遭受不必要的研究伤害。太小的干预研究将无法实现其科学目标,从而再次给研究参与者带来可能的伤害,而又不可能从知识的增长中获得相应的收益。对于观察性研究(如观察性研究)不会对参与者造成伤害的情况下,适当的权力可确保良好的时间和金钱管理。 美国国立卫生研究院(NIH)的大多数研究部门只有在受助人撰写了引人注目的准确的功效和样本量分析报告后,才会资助该研究项目。美国教育部的统计,研究和评估机构教育科学研究所(IES)还提供竞争性赠款,需要进行引人注目的准确的功效和样本量分析(目标3:功效和复制以及目标4:有效性/放大)。 在线课程结束时,学习者将能够: •使用框架和策略进行学习计划 •将研究目标写成可检验的假设 •描述纵向和多层研究设计 •编写统计分析计划 •规划子组的抽样设计,例如种族和民族 •证明招聘的可行性 •描述预期的缺失数据和辍学 •编写与计划的统计分析一致的功效和样本量分析 这是一个为期五周的密集互动在线课程。我们将结合使用教学视频,软件演示视频,在线讨论论坛,在线阅读,测验,练习作业和同行评审作业。最后的课程项目是您设计的同行评审研究,用于将来的功效或样本量分析。

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