1. Brief Introduction to Multilevel Analysis
Claudia Flowers

2. Influence of Social Groups

3. Lots of Schools

4. Nesting of Our Data What would be the unit of analysis? Students?
Spurious results
Teacher?
Fewer cases
School?
Much fewer cases

5. Conceptual Ecological Fallacy (Robinsons Effect)
Analyze at higher levels are used to form conclusions at a lower level—assume all members of a group exhibit same characteristics (e.g., stereotypes)
Atomistic Fallacy (Individualistic fallacy)
Formulating inferences at a higher level based on analyses at a lower level
Simpson’s Paradox
Erroneous conclusions may be drawn if group data from heterogeneous populations are aggregated and treated as a single homogeneous population
(illustration:

6. Multilevel Analysis Multiple names: multilevel analysis,
random coefficient model,
variance component model, and
hierarchical linear model.

7. Simple Conceptual Idea

8. Create Equations for Lots of Classrooms
And More

9. Simple Conceptual Idea

10. Use the Betas in Our 2nd Level

11. Interested? Multivariate statistics
Look at the last chapter in Steven’s textbook