I sometimes get questions about how to select the "best" model from experiments with blocks. We recommend that you model blocks as random effects, which means that you can't use Stepwise or Generalized Regression personalities for model selection because they only support fixed effects.
In this video I talk about:
- Why we block experiments
- Fixed versus random effects
- REML modelling
- Model selection strategies with random effects
I also mention the book, Optimal Design of Experiments: A Case Study Approach, as a good resource to learn more and the free chapter download that is available.
The example data table can be found from the attached JMP journal.
Let me know in the comments, below, if you have any questions.
Model Selection for Experiments with Blocks.jrn
