How to assess factor effects in a Mixture-in-mixture experiment?I have three formulations A, B and C each is a mixture of three components c1, c2 and c3; the component fraction in each formulation is different. How to design a three formulation A/B/C mixture experiment so that the effect of each component c on a response variable Y can be assessed?
Design of ExperimentsRe: How to assess factor effects in a Mixture-in-mixture experiment?Hi @frankderuyck,
I'm not sure about your question ?
- If you're interested about designing a mixture of mixture scenario, you can check the example here: Design of Experiments Example: A Mixture of Mixtures Design
- If you're interested about assessing relative factors importance on a response variable, you can check the parameters estimates from the fitted model, or assess variable importance through prediction profiler using Dependent Resampled Inputs or Linearly Constrained Inputs method (both methods should provide similar factor importance values).
Hope this answer will help you,
Re: How to assess factor effects in a Mixture-in-mixture experiment?Hi Victor, nice example!
Think there is a mistake in the second onstraint: Butter + Milk + Eggs
How to design when also the wet & dry ingredients also are variable mixture components e.g %Dry 30 - 45 and %Wet 40 - 55 ?
Re: How to assess factor effects in a Mixture-in-mixture experiment?Correction wet a dry limits above: what if %Dry 30 - 45 and %Wet 55 - 70 ?
Re: How to assess factor effects in a Mixture-in-mixture experiment?In this example, dry components should sum up to exactly 45%, hence the double constraints with 0,45.
But if you want to vary the dry content between 30 and 45%, you simply have to change the value to 0,30 in the second inequality constraint.
