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Re: st: Adjusted Standard Error in QIC Program
From
Joerg Luedicke <[email protected]>
To
[email protected]
Subject
Re: st: Adjusted Standard Error in QIC Program
Date
Fri, 25 May 2012 07:28:56 -0700
The way QIC is defined in Hardin & Hilbe (2003)*, you use the "naive"
variance estimates from a model assuming independent observations and
the robust variance estimates from a model with specified working
correlation. This is what the user-written program -qic- (version
1.1.9, from SSC) is doing, it fits two models and then uses the
variance estimates from both models (plus the quasi-likelihood from
the second model) to calculate the QIC. Thus, the difference in your
results is most likely due to fitting the same model with (via -qic-)
and without robust standard errors, and you should perhaps go with the
robust standard errors.
Have a look at Hardin & Hilbe (2003), p. 139ff. for information about
the QIC, and type in Stata -help vce_option- and follow the link to
the manual for robust variance estimation.
J.
*Hardin JW & Hilbe JM (2003): Generalized Estimating Equations. Boca
Raton, FL: Chapman & Hall/CRC.
On Thu, May 24, 2012 at 5:29 PM, Kenneth Shermock <[email protected]> wrote:
> I ran the user-developed QIC program today on a dataset and got puzzling
> results. First the output when using the xtgee command:
> xtgee out70250day group initgluccat unstablesocialhistory
> intx_unstablesocialhistory, family(binomial) link(logit) corr(ar1) force
>
> For our main variable of interest:
> Coeff=3D -0.50045
> Std err =3D 0.2235
> P=0.025
>
> I expected the results from the QIC program to be the same, but they are
> not.
>
> Output when using QIC program:
> qic out70250day group initgluccat unstablesocialhistory
> intx_unstablesocialhistory, i(mrn) t(date)family(binomial) link(logit)
> corr(ar1) force
>
> For our main variable of interest:
>
> Coeff=3D -0.50045
> Std err =3D 0.3062
> P=0.102
>
> I'm wondering if there is some glitch or if these results seem plausible.
> The only difference I see between the QIC and xtgee models is the QIC
> model "adjusts the std error for clustering" on one of my variables. What
> is this adjustment and is it plausible that it has such a profound effect
> on model estimates?
>
>
> Best regards,
>
> Ken
>
> Kenneth M. Shermock, PharmD, PhD
> Director, Center for Pharmaceutical Outcomes and Policy
> The Johns Hopkins Hospital
>
> Core Faculty
> The Armstrong Institute for Patient Safety and Quality
> Johns Hopkins Medicine
>
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