Interpreting Conditional Mixed process results
Dear Statalist
I have a system of equestions with four recursive types. The first endogenous dependent variable is a binary dummy, the Second dependent variable is censored, the third is continuous and the fourth is categorical. The simple representation of the model is as follow.
1. A = f(T.C)
2. R= f(A, X’)
3. Y= f(R,X’)
4. M= f(Y, X’)
X' is vector of explanatory variables and can vary in the respective equations
Cmp ( A= T,C) (R= A, X’) (Y=R, X’) (M= Y, X’),ind( $cmp_probit $cmp_censor $cmp_cont $cpm_catago)
I got the mixed regression output ( four estimation output). My problem is how to interpret the results.For example, I want to test the effect of A on M, then how can I interpret
I would be grateful if anyone can help me.
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