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TGYS Data Interpretation and Reporting Results
Peter Chen, PhDJulie Gibbs, BSW
Julie Maertens, MSJulie Sampson, MSStefanie Putter, BA
Objectives
Gain ConfidenceApply your KnowledgeMake Connections
Roadmap
Program evaluation reviewDiscussion of your data:
Desired evaluation results Factors affecting your results Comparison data
Next steps
Program Evaluation Cycle
1. Create logic model2. Decide on a design
3. Pick measurement tool4. Data analysis
5. Data reporting & reflection
Evaluation Terms
Sample/Sample Size Scale/MeasureSubscale Mean Comparison/Aggregate Data Norms
Statistical Terms
T-testP-valuep<.05Effect Size
Effect Size Benchmarks
<.20 = small
.21-.79 = moderate
.80-1.00 = large
Example
=
Pre-Tests: 55
Post-Tests: 38
Matched tests: 38
Sample Data Report
Coping Strategies Mean N Std. DeviationDesired Direction of
Change?Sig. Effect Size
Direct problem solving – PRE 2.64 739 0.68Yes 0.66 0.02
Direct problem solving – POST 2.66 739 0.68
Control – PRE 2.55 736 0.68Yes 0.01* 0.11
Control – POST 2.62 736 0.71
Support for feeling – PRE 2.35 737 0.83Yes 0.09 0.07
Support for feeling – POST 2.41 737 0.82
Support for actions – PRE 2.31 737 0.68Yes 0.00* 0.14
Support for actions – POST 2.41 737 0.69
Total coping strategies mean – PRE 2.45 741 0.59
Yes 0.01* 0.11Total coping strategies mean - POST 2.52 741 0.60
Potential Influences
Tracking
Data Management
AttritionConfidentiality
Your Sample
Participant Tracking
Data Management Fill in bubbles completely with pencil Fill in the entire administrative
sectionDon’t use photocopies
Comparison DataHow does your agency compare to other
TGYS grantees?Are you surprised by these differences?Would you expect these differences?
Results Justification
Results
People Effects
Program Effects
Next StepsDiscuss results with key staffLearn from other granteesContact your TGYS technical evaluator
CSU team contact information:
Julie Maertens: [email protected] Sampson: [email protected] Putter: [email protected]
You can also check out our website!
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