Is there a rule for selecting which experimental design one should carry out? I am new to statistics/ED and sometimes I find myself asking which design is best to use. My general guidelines have been (please correct if wrong):
- Use a Plackett Burman (PB) for screening the number of variables
- Use a fractional factorial if you have a large number of variables and cost/money is a factor as well as estimating effects
- Use an orthogonal design if your variables have different number of levels
- Use a full factorial if you do not have a large number of variables
Another sort of guideline I have is from here. I would like to have some input from members on their approach on this and if they do things differently.
EDIT: As per @Scortchi advice. Assuming you have a study which has 12 variables and another which 6 variables both with 3 levels for each variable. What type of design would you choose for each and why? The way i would approach this is by maybe screening the variables first as a full factorial would be too many cases to run then apply a full or fractional factorial. However I would then ask well why not do a orthogonal straight away. From the link i linked to earlier the objective of the design is a consideration so in the context of obtaining an optimal fit if you have +5 you would screen and then run a design, but why not run an orthogonal straight away. Hopefully this may be a bit clearer (apologies if the terminology I am using isn't correct)