[R] SEM with a categorical predictor variable
Lila234 at hotmail.de
Tue Apr 1 23:32:04 CEST 2008
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,
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