Is it possible to perform a good analysis of split plot/random effect DOE's with generalized regression? It can't handle random effects as is done with REML so is there a way to analyse correctly?
Hi Frank,
Have you tried running the analysis in Generalized Regression? You will find that you get an error if you try to run a model with a random effect using Generalized Regression personality:
The simple answer is no.
I have had a few people ask me about model selection for designed experiment analysis when you have random effects (usually due to blocking, but the same applies for whole plot random effects). I recorded a short video tutorial that might be useful.
I hope this helps,
Phil
I'm not sure exactly what question you are asking, but I suggest you read the following papers for ideas on how split-plots should be analyzed.
Box, G.E.P., Stephen Jones (1992), “Split-plot designs for robust product experimentation”, Journal of Applied Statistics, Vol. 19, No. 1
Bisgaard, Søren, (2000), “The Design and Analysis of 2 k-p X 2 q-r Split Plot Experiments”, Journal of Quality Technology, Vol. 32, No. 1, January
A split-plot experiment designed by JMP Custom Design should save a Model table script that will launch an analysis with a valid mixed effects model.
Can I use generalized regression with lasso or elastic net to analyse the split plot DOE results?
Thanks! The Bisgaard article looks interesting. My question simply is if split plot result analysis is possible with generalized regression, a great tool but I don't know if applicable on DOE results with random effets.
I know random effects do't work in generalized but I thought there might be away to overcome so I guess not.
Maybe it is better to use prior to REML Generalized regression with fixed random effects instead of Stepwise.
