Suppose I have some survey data on which I'd like to conduct an analysis
similar to this:
Yang, Age-period-cohort analysis, Ch 7.
Suppose further there are missing data I wish to handle via multiple imputation. Good practice requires that I include in the imputation model all the terms that I intend to include in the model of interest.
However, $\text{age} = \text{period}-\text{cohort}$.
I'm afraid this will cause problems for imputation software.
Has anyone else dealt with this issue? Any suggestions? I have access to software that can treat period and cohort as random effects, but I'm not sure that's enough to overcome collinearity with age.
Any guidance appreciated.