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
relationship (however, not necessarily), and
- they may have a common set of explanatory variables, while each
response variable may have its own independent covariates.
Additionally, if the two responses are not paired initially, but there
is/are a common covariate or two, is it a general practice to match the
responses according to those common covariates?
Or would anyone 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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