Richard Valliant <[email protected]>:
Maybe you want:
rcal (e1=) (w: e2), suuinit(D)
(i.e. leave out only the x not the =x)?
See also http://www.stata-journal.com/sjpdf.html?articlenum=st0050
On Thu, Dec 11, 2008 at 11:07 AM, Richard Valliant
<[email protected]> wrote:
> I'm a new user who is trying to fit a simple measurement error model to
> a set of estimates from two independent surveys. The surveys are
> measuring the same things. My data look like
>
> (e1, v1) = set of 30 estimates and their variances from survey 1
> (e2, v2) = set of 30 estimates and their variances from survey 2
>
> The model I want to fit is basic:
> e1 = a + b*e2 + u1
> e2 = E2 + u2 (u1 and u2 are the model errors, E2 is E(e2) )
>
> I've tried:
> mkmat v2
> mat D = diag(v2)
> rcal (e1) (w: e2), suuinit(D)
>
> This gives "invalid syntax". If I put some arbitrary variable x in the
> model (which I don't want), this works:
> rcal (e1=x) (w: e2), suuinit(D)
>
> But rcal apparently does not allow aweights to account for v1 =
> var(e1).
> Is there a way to use rcal or some other procedure to fit the model
> above, accounting for the fact that I have (1) estimates of variance for
> both e1 and e2 and (2) no covariates measured without error to put in
> the model?
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