[R] SEM with a categorical predictor variable

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


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

View this message in context: http://www.nabble.com/SEM-with-a-categorical-predictor-variable-tp16425959p16425959.html
Sent from the R help mailing list archive at Nabble.com.

R-help_at_r-project.org mailing list
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Received on Tue 01 Apr 2008 - 23:54:55 GMT

Archive maintained by Robert King, hosted by the discipline of statistics at the University of Newcastle, Australia.
Archive generated by hypermail 2.2.0, at Wed 02 Apr 2008 - 12:30:26 GMT.

Mailing list information is available at https://stat.ethz.ch/mailman/listinfo/r-help. Please read the posting guide before posting to the list.

list of date sections of archive