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Re: st: accessing delta-method-derived standard errors


From   "Scott Merryman" <scott.merryman@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: accessing delta-method-derived standard errors
Date   Wed, 11 Jun 2008 11:50:48 -0500

I believe that should be  -nlcom (exp(.5*[#2]_cons))-


Another way would be
-_diparm lnsig2u, level(`level') label("sigma_u")  function(exp(.5*@))
 derivative(.5*exp(.5*@))-

where the r(se) will contain the standard error.

Or (using at your own risk),
add the lines

-scalar sigma_se = r(se)- at about line #715 after the -_diparm
lnsig2u, level(`level') label("sigma_u")- line

and

-est scalar sigma_u_se = sigma_se- at about line #674 before the 	-
global XTL_madapt - line.

Now:

. sysuse auto,clear
(1978 Automobile Data)

. xtlogit fore mpg, i(rep) nolog

Random-effects logistic regression              Number of obs      =        69
Group variable: rep78                           Number of groups   =         5

Random effects u_i ~ Gaussian                   Obs per group: min =         2
                                                               avg =      13.8
                                                               max =        30

                                                Wald chi2(1)       =      4.62
Log likelihood  = -31.540725                    Prob > chi2        =    0.0316

------------------------------------------------------------------------------
     foreign |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         mpg |   .1462312   .0680197     2.15   0.032     .0129151    .2795474
       _cons |  -4.397192   1.712402    -2.57   0.010    -7.753439   -1.040945
-------------+----------------------------------------------------------------
    /lnsig2u |   .8701574   1.149525                     -1.382869    3.123184
-------------+----------------------------------------------------------------
     sigma_u |   1.545085   .8880564                       .500857    4.766404
         rho |   .4205076   .2801172                      .0708492    .8735078
------------------------------------------------------------------------------
Likelihood-ratio test of rho=0: chibar2(01) =     7.16 Prob >= chibar2 = 0.004

. disp e(sigma_u_se)
.88805638

Scott


On Wed, Jun 11, 2008 at 11:24 AM, E. Paul Wileyto
<epw@mail.med.upenn.edu> wrote:
> Check out the help on -nlcom-
>
> You would get the exponentiated version of the SE by using :
>
> -nlcom (exp([#2]_cons))
>
> That will transform the constant asscoiated with the second ML equation.
>
> To grab that value for other things, type -return list-
>
> and you should see the matrices and scalars generated by nlcom
>
> Paul
>
>
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