Dear all,
Would anyone suggest general multivariate models for two or more
strongly correlated (paired) dependent variables,
- when they may have different probability distribution (not
necessarily though),
- the nature of the correlation may be more complex (than a linear
correlation), and
- they may have a common set of explanatory variables, while each
response variable may have its own independent covariates (not
necessarily though).
Additionally, if the two responses are not paired initially, but there
is/are a common covariate or two, is it a common practice to match the
responses according to those common covariates?
Or does anyone can comment on the curds and whey method (Breiman and
Friedman), related to the above issues?
I will greatly appreciate any directly relevant comments, suggestions,
even some references.
Sincerely,
In-Sun
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