Design of experiment for 2 categorical factors and one continuous factorHi JMP experts
I struggle in deciding which DOE I should use for my experiment. I have 2 categorical factors ( 3 levels each), one continuous factor and the response is continuous (growth rate). The goal is to optimize the combination of these factors to get maximum growth.
What would be the best DOE to use?
I would appreciate your help!
Thanks!
A
DOERe: Design of experiment for 2 categorical factors and one continuous factorHi @ScientistNMC11,
From what you describe, you seem to already have screened out significant/important factors and want to optimize your response.
So you may be interested in Response Surface (but not very appropriate here since you have only one continuous factor) and I-Optimal designs.
With very few factors (and only one continuous) and a target to optimize one response, the easy way to design your DoE is by trying the "Custom Design". It will give you flexibility about which effects you want to see : main effects, interactions, quadratic effect for the continuous factor, ...
By doing so, you'll be able to have the best number of experiments depending on the level of details you want to have.
For example, if you want to estimate all main effects, interactions and the quadratic effect for the continuous factor, JMP recommends 27 runs (minimum 15 runs).
Depending on your experimental budget, you can add more runs (with replicates or by adding centre runs), or decrease the number of runs (by changing estimability of quadratic effect and/or interaction effects to "If Possible" instead of "Necessary"). You can also change the optimality criterion to I-optimal (red triangle next to Custom Design, Optimality Criterion).
At the end, always try several designs and compare them, to see how the design changes affect the prediction precision/variance, the aliases, the power for effects, ...
I hope it will help you 
Victor
Re: Design of experiment for 2 categorical factors and one continuous factorWithout alot more information it's problematic to recommend a specific experimental design. Just a few questions that need answers:
1. Do you have constraints on number of runs?
2. Are there any factor combination constraints?
3. How accurate and precise is the measurement system?
4. Are there any restrictions on randomization?
5. Is blocking or some other randomization constraint technique a good idea?
6. What model structure are you attempting to estimate?
And on and on...I'll let others add to the conversation.
Re: Design of experiment for 2 categorical factors and one continuous factorFirst, welcome to the forum. I think Pete's advice and line of questioning is right on.
Sorry if I have interpreted your query wrong, but it sounds more like you are trying to "pick a winner" rather than understand causal structure. You seem to want to use experimental design as a means of creating all off the possible combinations so you can pick the best combination. This is not how I would use experimental design. Design selection is best done after sufficient situation diagnostics have indicated what knowledge you have and what knowledge you need to get. The process is almost always iterative.
There may be some helpful information in this thread:
https://community.jmp.com/t5/Discussions/Simplifying-steps-in-DoE/m-p/479781#M72428
Re: Design of experiment for 2 categorical factors and one continuous factorHi Victor
Thank you so much for your reply!
By selecting custom design, I-optimal design and choosing to estimate all main effects, interactions (3rd) and RSM with number of center points 2 and number of replicates runs 3, I got a design of 24 runs and not 27 runs.
The max of the continuous factor is 0.5 and min is 0.05.
I am planning to use the design to conduct my experiment. Please let me know if I am missing something.
I appreciate your help!
Thanks.
A
