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Re: st: collinearity in categorical variables

From   "Mitchell F. Berman" <>
To   Stata List Server <>
Subject   Re: st: collinearity in categorical variables
Date   Fri, 26 Apr 2013 08:58:27 -0400

Thank you for the reply. Yes, I see that for a single categorical variable broken into dummy variables, collinearity between the dummy variables would be zero. But my question concerns correlation between related, similar, categorical variables.

If I have multiple similar categorical variables, for example: homebound, uses a walker, home-health aide, lives in nursing home, these categorical variables will move together though the data--- won't be identical for all patients, but correlated.

People mention standard VIF (which I know how to do), but the more thorough answers imply this is not correct.

This links suggests perturb (a module available for Stata, R, and SPSS) or polychoric correlation

This link from talkstats suggests that polychoric correlations (available in R) are preferable, because correlations calculated using pearson product moment are invalid for categorical data.

someone else suggested spearman correlation coefficient

factor analysis

This is beyond my level of theoretical understanding. I was trying to get a sense of what the experts on the Stata List server use.

Thank you for any additional input.


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