R help - Mar 2011 - binary exogenous variable in path analysis in sem or lavaan

Hello all

I'm trying to run some path analysis in either sem or lavaan (preferably
lavaan because I find its interface easier to use). Most of my variables are
continuously distributed and fairly well-behaved but I have a single exogenous
variable (sex) which is not continuously distributed. Preliminary model fitting
suggests that there aren't any sex by (anything else) interactions. The two
approaches to dealing with this that I've come up with are to code it as a
numerical variable (1 & 2 for female and male) and run the analysis as
normal, or to run two separate models, one for males and  one for females.
I'd prefer to do the former because it will make interpretation easier and
also give a larger sample size for the model fit but I'm not sure how
acceptable that is. I know that some SEM packages are able to cope with
categorical variables - is there any way to do this in R?

Thanks for any help

Regards

Rob

Rob,

If 'sex' is indeed an exogenous variable (ie. predictor only), you can
simply code it as (1=male, 2=female) and use it as a covariate in any sem
model. In lavaan, you can explicitly use the argument 'fixed.x=TRUE',
which
will regard all exogenous covariates as fixed variables. Their
means/variances/covariances are not included in the model estimation (so
they do not have to be normally distributed), but they are simply set at
their sample values. In essence, this is exactly what happens in ordinary
regression, when a categorical predictor is recoded as a dummy variable.

Yves.

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