Rehabilitation Research Boot Camp: Statistical Analysis

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Many clinicians struggle with applying their research design and statistical knowledge to the research articles they read. Many find that the principles of what statistical analyses tell them is simply not intuitive enough nor do they apply them frequently enough to feel comfortable with the process of linking stats to specific clinical questions. This course will specifically address these concerns by discussing the major considerations in statistics and applying these consideration to clinical problems in order to enhance the participants understanding of how to interpret research findings.

Meet your instructors

Chad Cook

Dr. Cook is a professor at Duke University with a Category A appointment in the Duke Clinical Research Institute and an adjunct appointment in the Department of Population Health Sciences. He is a clinical researcher, physical therapist, and profession advocate with a long history of clinical care excellence and service and…

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Ken Learman

Ken Learman, PT, PhD, OCS, COMT, FAAOMPT is a Professor of Physical Therapy at Youngstown State University where he is responsible for teaching manual therapy, patient examination and clinical reasoning, and research design and data analysis in the curriculum. Ken is also affiliated faculty at Duke University Division of…

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Chapters & learning objectives

1. Understanding Statistical Analysis

Chapter one introduces the learner to the foundations of statistical analysis including the advantages of developing a research team. This course will also describe the fundamentals of statistical analyses and how these probabilistic estimates apply to research design

2. Understanding and Describing Data

Chapter two will identify the different types of data and how an investigator chooses statistical procedures based on data types. The learner will also be able to understand and describe the different types of variables and their importance in the statistical analysis upon completion of this chapter

3. Parametric and Non-Parametric Statistics

Chapter three will compare and contrast the assumptions of both parametric and non-parametric statistics and why each category is advantageous for different types of data. A description of how each category of statistics uses a different approach to test a similar construct of probability will be provided. In addition, differences in output including statistical power will be explained.

4. Studies of Differences

Chapter four will introduce the learner to various statistical models used for studies of differences. The module will include models of parametric versus non-parametric examples for between groups as well as within group differences. The learner will also be introduced to more complex two-way designs where between groups and within groups or covariates are included.

5. Studies of Associations

Chapter five will cover key characteristics for studies of association and what statistics would be most appropriate for creating a model.

6. Clinical versus Statistical Significance

Chapter six will describe and value other statistical procedures used in biostatistics used to answer questions regarding concepts such as number needed to treat, survival analysis, factorial designs and more

7. Summary

Chapter eight will summarize the content contained in the statistics for rehabilitation research course and provide additional resources the learner can procure to garner further training.

More courses in this series

Rehabilitation Research Boot Camp: Understanding Research Methodology

Chad Cook

Rehabilitation Research Boot Camp: Research Priorities & Study Types

Chad Cook