Power and Sample Size for Multilevel and Longitudinal Study Designs
University of Florida via Coursera
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Overview
Class Central Tips
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.
Taught by
Albert Ritzhaupt
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Reviews
3.0 rating, based on 1 reviews
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This course ONLY covers the topic of how to use a software package to calculate the power of a designed study, or the sample size needed for an experiment with a specific power. It DOES NOT cover any formulas of how to calculate it. The course DOES NOT include how to analyze or interpret data. If you are looking for methods or formulas, this is not the course. Some lectures are highly repetitive for basic concepts such as correlation, however more advance concepts (such as contrasts) are not explained. This course could be a three weeks course instead of five weeks.