University of Florida - Power and Sample Size for Multilevel and Longitudinal Study Designs
- Offered byCoursera
Power and Sample Size for Multilevel and Longitudinal Study Designs at Coursera Overview
Duration | 24 hours |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Intermediate |
Official Website | Explore Free Course  |
Credential | Certificate |
Power and Sample Size for Multilevel and Longitudinal Study Designs at Coursera Highlights
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Intermediate Level Course participants should have successfully completed an introductory statistics course prior to enrolling in the online course.
- Approx. 24 hours to complete
- English Subtitles: English
Power and Sample Size for Multilevel and Longitudinal Study Designs at Coursera Course details
- 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.
Power and Sample Size for Multilevel and Longitudinal Study Designs at Coursera Curriculum
Week 1: Introduction to Multilevel and Longitudinal Designs
1.0 Course introduction and overview
1.1 Review of basic statistical concepts
1.2 Introducing longitudinal studies
1.3 Studies with a single level of clustering
1.4 Studies with multiple levels of clustering
1.5 Multilevel and longitudinal studies
Guided practice of GLIMMPSE software 1
Pre Survey
Week one lecture notes
Power or sample size analysis problem 1
Practice assessment with feedback 1
Graded assessment 1
Power and sample size analysis quiz 1
Week 2: Foundations of Complex Multilevel and Longitudinal Designs
2.0 Within and between independent sampling unit factors
2.1 Understanding the hypothesis
2.2 Power and type I error
2.3 Choosing the test
2.4 Correlation structure
Guided practice of GLIMMPSE software 2
Week two lecture notes
Power or sample size analysis problem 2
Practice assessment with feedback 2
Graded assessment 2
Power or sample size analysis quiz 2
Week 3: Model Assumptions, Alignment, Missing Data, and Dropout
3.0 Model assumptions
3.1 Alignment of power and data analysis
3.2 Predicting missing data and dropout
3.3 Accounting for missing data and dropout
3.4 Continuous, binary and Poisson outcomes
Guided practice of GLIMMPSE software 3
Week 3 lecture notes
Power or sample size analysis problem 3
Practice assessment with feedback 3
Graded assessment 3
Power or sample size analysis quiz 3
Week 4: Inputs to Analysis, Recruitment Feasibility, and Multiple Aims
4.0 Inputs for power analysis: Literature review
4.1 Inputs for power analysis: Internal pilot studies
4.2 Inputs for power analysis: Planned pilot studies
4.3 Studying power via simulation
4.4 Demonstrating recruitment feasibility
4.5 Handling multiple aims
Week 4 lecture notes
Power or sample size analysis problem 4
Practice assessment with feedback 4
Graded assessment 4
Power or sample size analysis quiz 4
Week 5: Ethics and Using Power and Sample Size Analysis to Get Funded
5.0 Ethics of power and sample size
5.1 Writing the sample size section for your grant
5.2 Graphics for power and sample size
5.3 Power for subgroup analysis
5.4 Getting funded
Week 5 lecture notes
Power or sample size analysis problem 5
Course Evaluation & Post Survey
Practice assessment with feedback 5
Graded assessment 5
Power or sample size analysis quiz 5
Final course examination
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