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Re: st: mvn impute - collinear imputation (dependent) variables detected

Subject   Re: st: mvn impute - collinear imputation (dependent) variables detected
Date   Mon, 17 Oct 2011 17:38:18 -0500

Raquel Guimaraes <> asked about using -mi impute mvn-
with collinear imputation variables:

> I need help using multiple imputation command for Multivariate Normal
> Distribution. I did this before and worked perfectly. Now, unfortunately, I am
> getting the following error message: collinear imputation (dependent)
> variables detected. Below you may find the piece of do-file. 


> mi impute mvn: collinear imputation (dependent) variables detected

> Well, what I am supposed to do? I have only one dependent variable (leitura),
> and I can not drop it. 

The dependent variables in -mi impute mvn- are actually the variables to be
imputed---the left-hand-side variables.  Raquel will need to remove the
collinear variable "climadisciplinar_mean" from the left-hand side.

Even though the note in the output says that the variable was "omitted because
of collinearity," the variable has not yet been omitted.  The note is a generic
note printed by the command -_rmcoll-, which checks for collinearity.  Collinear
variables on the right-hand side are automatically omitted, but left-hand-side
variables are not.  The note is printed to help users decide on their own which
left-hand-side variables to remove.

If Raquel would rather keep the variable "climadisciplinar_mean" in the model,
she can instead drop other collinear imputation variables.  Raquel can use the
command -_rmcoll- on any list of variables to determine which variables in the
list form a non-collinear set.



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