If you fit a block as a fixed effect in a saturated model, and its effect is not significant after you reduce it via stepwise regression, do you need to add it back to the model?
This was posted to the JMP blog yesterday where Phil Kay describes reducing a saturated model with a block effect. He says the random block should be added as a fixed effect 1st in this specific case, then after you reduce the model via stepwise regression, you should re-fit the reduced model & add the block as a random effect. In his example the block was significant after he reduced the model. I...