If you ask the same question repeatedly, the
answer is likely to be the same.
On your first, when Alan says "any numeric variable"
he means what he says. -loneway- doesn't have options
for indicating what kind of variable you have, and
Stata doesn't have any inbuilt way of working that
out. How could it?
Thus the help for -oneway- gives an example in which
-mpg- is the response. Many of us would be happy
to class -mpg- as a continuous variable that happens
to be reported as integers, at least in the auto
dataset bundled with Stata. But -loneway- doesn't know that, and the
results would be the same if -mpg- were the name
of a discrete variable that contained say counts or
even categorical codes. Those results may or may not
be what you want.
On variance components in Stata in general, the whole story
of what is easily available is obtainable from
-findit variance components-.
Nick
[email protected]
> Thanks for your reply.
>
> When you indicate that "the dependent variable can be any
> numeric variable"
> for -loneway-, do you mean continuous variables, right? How
> to examine
> variance
> components for binomial/ordered/multinomial variables such as
> occupational group then?
"Feiveson, Alan H. (JSC-SK311)" <[email protected]>:
> > -loneway- works only with first and second moments of the
> data and thus
> > will unbiasedly estimate between and within variance components,
> > regardless of the distribution of the data (as long as it
> it numeric).
> > The dependent variable can be any numeric variable.
> >
> > -xtreg- assumes the within- and between-class errors come
> from normal
> > distributions and estimates their variances by maximum
> likelihood with a
> > GLS regression model. So if the data is not normally
> distributed, you
> > can get completely different results and -xtreg- is not to
> be believed.
> > However in this case the value of knowing values of
> variance components
> > is questionable. On the other hand, if the data really are normal,
> > -xtreg- should be more efficient than -loneway-.
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