Calculate D-efficiency of an experimental desgin in R

问题

I have an experimental design. I want to calculate its D-efficiency. I thought R package AlgDesign could help. I found function optFederov which generates the design and - if the user wants - returns its D efficiency. However, I don't want to use optFederov to generate the design - I already have my design! I tried eval.design(~.,mydesign). But the only metrics it gives me are: determinant, A, diagonality, and gmean.variances. Maybe there is a way to get from determinant or A to D-efficiency (I am not a mathematician, so I am not sure). Or maybe some other way to calculate D-efficiency "manually" so to say?

Thanks a lot for any hint!

回答1:

I was working on a similar project. I found out this formula Deff = (|X'X|^(1/p))/ND in this link. Where X is the model matrix, p is the number of betas in you linear model and ND the number of runs your experiment has. You could just make a code like this and it will do the trick.

det(t(X)%*%X)^(1/beta)/(numRuns)

I tested the results using JMP for my project so I believe this is the correct formula

来源：https://stackoverflow.com/questions/29176456/calculate-d-efficiency-of-an-experimental-desgin-in-r