D Studies
Ralph Bloch edited this page May 7, 2023
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11 revisions
Whereas G Studies determine the G Coefficients of an actual test, D Studies help with 'what if' scenarios, i.e. in finding most cost effective designs for actual tests, based on preliminary variance components from pilot studies.
Once we know the variance components, the G Coefficients depend only on the sample sizes of the facets of generalization by simple arithmetic calculations.
So let's look at the result of the G Study:
Now let's look how we do a D Study:
Youtubes
- Generalizability Analysis I: Facets & Variance
- Generalizability Analysis II: Systematic Bias
- Generalizability Analysis III: Missing Data, and Replications
- Installing G-String in MacOS
For G_String_M users*
- Using G_String_M
- Understanding Generalizability Analysis
- Explore Generalizability Analysis with R
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