Introduction to Multilevel Modeling is a two-day (9/27/23 and 9/29/23) course focused on the application and interpretation of multilevel models, also known as hierarchical linear models and mixed models, for the analysis of nested data structures.

Nesting can arise from hierarchical data structures (e.g., siblings nested within family; patients nested within therapist), longitudinal data structures (repeated measures nested within individual), or both (repeated measures nested within patient and patient nested within therapist).

It is well known that the analysis of nested data structures using traditional general linear models (e.g., ANOVA or regression) is flawed, oftentimes substantially so: Tests of significance are likely biased and within- and between-group effects are confounded with one another. All of these limitations can be addressed within the multilevel model.

This workshop provides an introduction to the application of multilevel models with nested data, including software implementation in SAS, SPSS and Stata.

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Integrated Mixed Methods: Bridging Qualitative and Quantitative Methods and Results

This course will take place over three mornings (9/25/23, 9/27/23, and 9/29/23), 2.75 hours per morning, and will be offered via Zoom. Attendance is required as the course will not be recorded.

Integrated mixed methods are used to answer questions that necessitate more than one method to achieve a holistic understanding. Combining qualitative and quantitative approaches can enhance conversations about theory, practice, and/or policy. This demanding paradigm requires knowledge, skill, and expertise in quantitative and qualitative methods, as well as the art of intentionally integrating the approaches to and findings from each mode of inquiry.

This course focuses on strategies, tips, and best practices to accomplish integration in accessible and effective ways, including:
- Rationales to guide decision-making related to study design and execution
- Conceptual, theoretical, and/or logic models as roadmaps to set the stage for and guide integration
- Analytic strategies that advance frameworks and dynamic processes of connecting, building, merging, embedding, and bridging

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Navigating the Use of Patient-Reported Outcomes in Research and Practice: The PROTEUS Consortium

This NIH Collaboratory Rethinking Clinical Trials Grand Rounds features:

Claire Snyder, PhD
Professor
Johns Hopkins Schools of Medicine and Public Health

Norah Crossnohere, PhD
Assistant Professor
Ohio State University College of Medicine

Anne Schuster, PhD
Research Scientist
Ohio State University College of Medicine

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