# Re: st: svy variance estimation: delete 1 jackknife & svymlogit and syvclogit?

 From [email protected] (Jeff Pitblado, StataCorp LP) To [email protected] Subject Re: st: svy variance estimation: delete 1 jackknife & svymlogit and syvclogit? Date Mon, 18 Jul 2005 09:48:08 -0500

```Alexander Cavallo <[email protected]> asks two general questions
about the survey data capabilities in Stata:

1.  What happens when you use -svy jackknife- with data from a design with 2
PSUs in each stratum?

2.  Why isn't there a -svyclogit- command?

*****************************************************************************
Question 1:

> I am using complex survey data with stratified and clustered design.  I
> have over 200 strata and 2 PSUs per strata (or are these clusters??).
>
> If I want to use the delete 1 jackknife for variance estimation, wouldn't
> each replication involve a strata with a singleton PSU?

Yes.  However -svy jackknife- uses the "replicated" point estimates from the
delete-1 fits to compute it's own variance estimator for the model parameters.
These delete-1 fits do not employ the linearized variance estimator; in fact,
the variance from each of these delete-1 fits are entirely discarded.

> Can I do jackknife variance estimation in this case?

Yes, the above procedure works.

> Could I drop an entire strata and use the jackknife calculations for delete

Only if you change the way you -svyset- your data.  I'm not recommending this,
but you could treat your strata variable as a PSU variable in your -svyset-,

*****************************************************************************
Question 2:

> I am interested in estimating the CLOGIT model with complex survey data. I
> am estimating a choice model with some variables that are attributes of
> the choice X(j) and others that are characteristics of the individual
> Z(i).
>
> The model is
>
> Pr(i choses j) = exp[beta*X(j) + gamma(j)*Z(i)] / sum k=1 to M {
> exp[beta*X(k) + gamma(k)*Z(i)}
>
> The model can be estimated by converting the data to long format where
> each observation becomes M observations with a single instance of the
> indicator S=1 for the chosen category.  To estimate the gamma(j)
> paramaters I need to create interactions of Z(i) with with dummy variables
> for the choices.
>
> I am planning to use jackknife deletion of one PSU to estimate the
> variance of the parameter vector.
>
> My questions are:
>
> Why is there no svyclogit - is there a theoretical reason that it is not
> implemented?

No.  Until recently there were some technical reasons why we hadn't
implemented -svy: clogit-.  I can make no guarantee, or even give a timeline;
but we are working to get the -svy- prefix to work with other estimation
commands, including -clogit-.

For the time being, you can use -svy jackknife- with -clogit- in the following
way:

1.  Make sure to -svyset- using -iweights- instead of -pweights-, -clogit-
currently will not accept -pweights-.

2.  Prefix your call to -clogit- with -svy jackknife _b:-, this will bypass
-svy jackknife-'s check for supported estimation commands.  This allows users
to experiment with -svy-'s resampling methods on commands that are not
identified as supported.

3.  Use -svy- to replay the estimation results, -clogit- does not recoginize
survey estimation results and does not display a proper header.

--Jeff
[email protected]
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