How does the correlation constraint "cc" affect the correlation of mismatch parameters

Hello,

I am using the correlation constraint to tie together Monte-Carlo mismatch parameters for a number of instances of an ADC.

Example syntax 

statistics {
correlate dev=[ I0.* I1.* ] cc=1.00
}

When cc=1 I can see that the parameters are all identical across instances.

When cc=0 the parameters are uncorrelated and I have full Monte-Carlo dispersion has per the model distributions.

Are values between 0 and 1 valid?

I would like to reduce the amount of mismatch between certain instances with the idea being that my blocks aren't too far away from each other so perhaps my mismatch should not be maximum.

Is this a valid approach? I haven't yet found any documentation that describes the values for "cc" and in my testing it's not obvious to me how cc affects the correlation for values between 0 and 1.

Thanks for your help.

Matthew Cordrey-Gale