What is the most appropriate method for analyzing clustered data (i.e., repeated measurements nested within subjects) when there are very few clusters (e.g., 3 subjects)?
Here's a brief description of the study:
- There are 3 subjects, each experiencing 5 conditions.
- Within each condition, there are 12-15 repeated measures.
- The measures are: the number of responses on two alternatives (B1 and B2) and number of reinforcers earned for each type of response (R1 and R2).
The question is how subjects allocate responses to the two alternatives (B1 and B2) based on the number of reinforcers earned under those alternatives (R1 and R2).
The image below provides examples of some possibilities.