1 reply to this topic

[dan.hines]

I am trying to use a healthy volunteer population PK model in a monte carlo simulation to calculate a probability of target attainment analysis. In order to do this I need to inflate the variability of my clearance value to be more representative of a patient population. This is standard practice and easy for me when I have a diagonal omega matrix. But in this model, my omega matrix (covariance matrix) has off diagonal omega values associated with clearnace. So if I want to double the %CV value for clearance, and then in turn omega values, how do I calculate the impact of this clearance inflation on the off diagonal omega values?

[smouksassi1]

you can keep the correlation matrix as is and inflate the stdev part:
...

 

user R on any other software to compute your "new " var cov matrix based on:

inflationfactor <- 1.15

mu <- c(0, 0, 0) # eta means

 

# this is your correlation matrix of omega

corMat <- matrix(c(1, 0.78, 0.23,

0.78, 1, 0.27,
0.23, 0.27, 1),
ncol = 3)

 

# you diagonals squareroots

stddev <- c(1.23, 0.92, 1.32) * inflationfactor


covMat <- stddev %*% t(stddev) * corMat

 

plug the new covMat into your pml code