1. Individual Consultation

2. Purpose/ Process
Individual study or program of study that will be conducted, or submitted for funding in the next 12 months.
Your interest area
Specific study
Development of grant proposal

3. Group Activity

4. Purpose Integrate Institute Competencies Development of logic model
Construction of single-case design given a research question
Application of visual analysis with modest or non-perfect data
Application of randomization
Application of statistical analysis to define effect size

5. Process: Monday Study 1: build logic model Form groups
Select research question (s)
From provided lists OR developed by group
Research questions need to allow use of at least two types of single- case designs.
Study 1: build logic model
Research Question A
Research Question
Research Question A
Study 1
Study 2
Study 1
Study 2

6. Process: Tuesday Study 1 and Study 2: Diagram research designs
Develop two data sets for each study
Data Set A = clear functional relation
Data Set B = modest or questionable relation
Write a paragraph for each data set describing the visual analysis: Study 1 (Data Set A, Data Set B) Study 2 (Data Set A, Data Set B). Do the data document a functional relation that warrants publication (e.g. three demonstrations of a basic effect, each at a different point in time)? Note limitations to the data patterns that may weaken demonstration of an effect.
For ABAB: Level, trend, variability, immediacy of effect, overlap and consistency across similar phases.
For MBL: Add vertical analysis at points of intervention
For ATD: Magnitude and consistency of separation

7. Process: Wednesday Select Research Question for Study 3
You may use a new research question or a research question used for Study 1 or Study 2.
But if you use a prior question, plan to start the design process anew.
Define the logic model for this research question
Define steps for incorporating randomization into the design/analysis
Define how masked visual analysis may be incorporated
Build a data set of projected data(Data Set C) for the design that defines a “modest/questionable” effect.
Build Excel file of Data Set C
Set up ExPRT to interpret the results
With assistance from John and Joel

8. Process: Thursday
Complete ExPRT analysis with projected data provided by Joel and John
Using Data Set C
Calculate NAP (rescaled)
Define how you would apply multi-level modeling to assess effect size
Develop a 10 min presentation for Data Set C
Research Question
Logic Model
Design
Interpretation of modest/questionable Data Set C
Visual analysis
Randomization
NAP (rescaled)
Multi-level modeling potential

9. Process: Friday
Deliver presentation Friday Morning to full Institute.