Sorry if this question has been asked previously, I searched but found
little. There also doesn't seem to be a dedicated SEM list-serv so hopefully
this will find its way to the appropriate audience.
In discussing SEM with a colleague I mentioned that a model they were
fitting in AMOS was equivalent to a linear regression and that the
coefficients would be the same. This of course was the case. However, the
standard errors associated with the paths differed dramatically between
{sem} and AMOS and each from {lm}. Specifically, AMOS produced smaller
standard errors with z's/cr's differing by around half a point from {sem},
which could substantially alter one's conclusions.
I searched a bit and found no real information on how std. errors were being
calculated for either AMOS or {sem}. I assume that the estimates of std.
errors for lm followed normal regression methods. I also assumed that sem
and lm differed based on the former being fit using nlm and thus being due
to asymptotic versus exact estimates. But, does anyone have information
about how sem and AMOS are calculating standard errors and why they would
differ rather dramatically?
SEM is really not appropriate for the dataset in question but the
discrepancy in standard errors made me curious.
Thanks a lot for any help,
Ned Dochtermann
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