[R] SEM with a categorical predictor variable

From: Lila86 <Lila234_at_hotmail.de>
Date: Tue, 01 Apr 2008 14:32:04 -0700 (PDT)

Hi,

we are trying to do structural equation modelling on R. However, one of our predictor variables is categorical (smoker/nonsmoker). Now, if we want to run the sem() command (from the sem library), we need to specify a covariance matrix (cov). However, Pearson's correlation does not work on the dichotomous variable, so instead we produced a covariance matrix using the Spearman's (or Kendalls) correlation method, which works.

Running the sem() command on our model using that covariance matrix works fine, but I am not sure if it was okay to make the covariance matrix using Spearman or Kendall. Can we interpret the regression coefficients that we find in summary(sem) just as if we had used Pearsons correlation in the covariance matrix? Or is there any other way to define a SEM including categorical variables without using a covariance matrix?

I appreciate every help. Thank you very much, Vera

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Received on Tue 01 Apr 2008 - 23:54:55 GMT

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