Re: st: margins: (not estimatable)

[D-Ta <altruist81@gmx.de>]

Wonderful, thanks for your support!!

Am 13.07.2011 21:09, schrieb Jeff Pitblado, StataCorp LP:
> Darjusch<altruist81@gmx.de>  is using -margins- after a -logit- model that
> contains the interaction of a single factor variable with the linear,
> quadratic, and cubic terms of a continuous variable and is getting the
> '(not estimable)' label in the -margins- output:
>
> > I have read a similar thread
> > (http://www.stata.com/statalist/archive/2011-06/msg00407.html), but the
> > answer wouldnt solve my problem, I run a logit model where I am
> > interested in the marginal effect of fail (dummy) on dropout at the
> > value of mc_1styr_c==0 (the model is based on a regression discontinuity
> > research design).
> >
> > Here is what I do:
> >
> > . logit dropout3_en i.fail##(c.mc_1st##c.mc_1st##c.mc_1st) if  sex==0,
> > vce(cluster mc_1st)
> >
> > (output omitted)
> >
> > . margins ,dydx(fail) at(mc_1st==0)
> >
> > Conditional marginal effects                      Number of obs   =
> >      409
> > Model VCE    : Robust
> >
> > Expression   : Pr(dropout3_enrollment), predict()
> > dy/dx w.r.t. : 1.fail
> > at           : mc_1styr_c~d    =           0
> >
> > ------------------------------------------------------------------------------
> >                |            Delta-method
> >                |      dy/dx   Std. Err.      z    P>|z|     [95% Conf.
> > Interval]
> > -------------+----------------------------------------------------------------
> >         1.fail |  (not estimable)
> > ------------------------------------------------------------------------------
> > Note: dy/dx for factor levels is the discrete change from the base level.
> >
> >
> >
> > The command: margins ,dydx(fail) at(mc_1st==0) should give me the effect
> > and the significance level of interest. If I enlarge the sample (lets
> > say, not condition on sex==0) it works.
> >
> > Could someone explain me the core of the problem and how to solve it?
>
> The check for 'Estimable functions' performed by -margins- is detailed in the
> methods and formulas section of -[R] margins-.
>
> The basic idea here is that -logit- saves off a hidden matrix, let's call it
> H, that -margins- uses to check for estimable functions.  This H matrix should
> only contain values -1, 0, and 1.  The check is as follows
>
> 	z*b is estimable if z = z*H
>
> where b is the coefficient vector, and z a vector of fixed/hypothetical values
> of the independent variables in the fitted model. -margins- compares z and z*H
> via relative differences with a numeric tolerance of 1e-5, controlable via the
> -estimtolerance()- option.
>
> We suspect that the cubic polynomial in Darjusch's fitted -logit- model is
> causing the H matrix to have values outside -1, 0, and 1.  This can happen
> with numerically unstable calculations due to huge scale differences between
> the independent variables, otherwise caused by the result of the propagation
> of errors in the finite precision calculations.
>
> Darjusch can verify if there are problems with the H matrix by typing the
> following Stata commands after the -logit- model fit:
>
> 	. matrix H = get(H)
> 	. matrix list H
>
> If the output has values other than -1, 0, and 1, Darjusch can use the
> -noestimcheck- option with -margins- to prevent the estimability check.  We
> feel confident in giving Darjusch this advice in this case since there is only
> one factor variable in the model specification, and the polynomial terms of
> the continuous variable should not, in theory assuming infinite precision
> calculations, result in non-estimable functions.
>
> --Jeff
> jpitblado@stata.com
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