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Re: st: Using the 2008 American National Election Study with Stata v.11


From   Austin Nichols <austinnichols@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Using the 2008 American National Election Study with Stata v.11
Date   Thu, 15 Oct 2009 12:19:03 -0400

Peter Wielhouwer <peter.wielhouwer@wmich.edu> :
You can also use a geographic id as a clustering variable if PSU is
unavailable--or even if PSU is available and PSUs are nested within
geography and you think there is clustering by geography.

. u anes2008_2009panel_dataset, clear

. svyset [pw=wgtbase]

      pweight: wgtbase
          VCE: linearized
  Single unit: missing
     Strata 1: <one>
         SU 1: <observations>
        FPC 1: <zero>

. svy:ta w10p4, ci
(running tabulate on estimation sample)

Number of strata   =         1  Number of obs      =       619
Number of PSUs     =       619  Population size    = 610.10636
                                Design df          =       618

-------------------------------------------------
w10p4.    |
Favor or  |
oppose    |
raising   |
taxes on  |
incomes   |
over      |
200k/yr   | proportions           lb           ub
----------+--------------------------------------
 1, Favor |        .381        .3393        .4245
 2, Oppos |       .0682        .0496        .0931
 3, Neith |       .5508        .5066        .5943
          |
    Total |           1
-------------------------------------------------
Key:  proportions  =  cell proportions
      lb           =  lower 95% confidence bounds for cell proportions
      ub           =  upper 95% confidence bounds for cell proportions

. egen c=group(stratum cdstate), mi label

. svyset c [pw=wgtbase]

      pweight: wgtbase
          VCE: linearized
  Single unit: missing
     Strata 1: <one>
         SU 1: c
        FPC 1: <zero>

. svy:ta w10p4, ci
(running tabulate on estimation sample)

Number of strata   =         1   Number of obs      =       619
Number of PSUs     =        81   Population size    = 610.10636
                                 Design df          =        80

-------------------------------------------------
w10p4.    |
Favor or  |
oppose    |
raising   |
taxes on  |
incomes   |
over      |
200k/yr   | proportions           lb           ub
----------+--------------------------------------
 1, Favor |        .381        .3383        .4255
 2, Oppos |       .0682        .0513        .0903
 3, Neith |       .5508        .5098        .5912
          |
    Total |           1
-------------------------------------------------
Key:  proportions  =  cell proportions
      lb           =  lower 95% confidence bounds for cell proportions
      ub           =  upper 95% confidence bounds for cell proportions



On Thu, Oct 15, 2009 at 9:22 AM, Nick Winter <nwinter@virginia.edu> wrote:
> The ANES weights should be used as pweights.
>
> In recent studies (eg, the 2004 dataset), ANES supplies a variable that
> indicates "strata" and "psus" that can be used for BRR or Taylor-series
> approaches to variance estimation.  (They don't release the complete
> sampling information to prevent possible identification of individual
> respondents -- this is discussed, eg, in the introductory materials for the
> 2004 study documentation:
> http://www.electionstudies.org/studypages/2004prepost/nes04int.txt)
>
> So until the final,complete release of the 2008 data, you are stuck with
> just using the appropriate pweight.
>
> (As an aside, in my experience, taking proper account of the stratification
> and clustering in the ANES datasets has not had dramatic effects on standard
> errors.  But of course my prior experience doesn't guarantee your future
> performance....)
>
> - NW
>
> sjsamuels@gmail.com wrote:
>>
>> It states that "comprehensive instructions will accompany the full
>> release of the Panel Study Data."
>>
>>  I'm not familiar with ANES, but neither the paper Bob found nor the
>> user guide have anything about weights centered at zero. (The paper
>> does recommend that weights be scaled so that they sum to 1.)  In
>> fact, weights<0 would be rejected by any survey program.
>>
>>
>> -Steve
>>
>>
>> On Thu, Oct 15, 2009 at 6:07 AM, Peter Wielhouwer
>> <peter.wielhouwer@wmich.edu> wrote:
>>>
>>> Subject: Re: st: Using the 2008 American National Election Study with
>>> Stata
>>> v.11
>>>
>>> Thanks, Richard. I've been looking through the SVY manual, but what the
>>> ANES
>>> dataset provides are individual weighting variables (post estimation
>>> weights
>>> centered on zero, as described in the paper you pointed me to. I agree
>>> that
>>> it would be nice for ANES to be more specific about how to use Stata well
>>> with the dataset.
>>>
>>>
>>> At 04:20 PM 10/14/2009, Peter Wielhouwer wrote:
>>>
>>>> Is anyone familiar with using the 2008 NES with Stata? I have two
>>>> specific questions:
>>>>
>>>> 1. Which weight command is most appropriate for the data? Based on the
>>>> Stata UG, it seems that the -iweight- syntax is most appropriate, but is
>>>> that correct?
>>>
>>> I am not familiar with the data set, but I would be amazed if
>>> iweights were the way to go.  My guess is you want pweights. googling
>>> around found this recent paper:
>>> ftp://ftp.electionstudies.org/ftp/nes/bibliography/documents/nes012427.pdf
>>>
>>> If you google around some more though, maybe you can find something
>>> easier to wade through; it is nice when a data set explicitly tells
>>> you how to set the weights in Stata.
>>>
>>>> 2. In the ANES 2008 user guide, we are advised, "due to the complex
>>>> sample design of the ANES, sampling errors and related statistics
>>>> (including confidence intervals, p-values, t-tests, and all other tests
>>>> of statistical significance) should not be calculated using methods
>>>> intended for simple random samples." In light of this, which would be
>>>> the appropriate statistics to use in Stata?
>>>
>>> I think the correct question is not what statistics should I use, but
>>> what statistical methods should I use to get the correct
>>> statistics.  Since you have Stata 11, you should also have the SVY
>>> manual available in pdf form.  Just click help/ PDF
>>> documentation.  If bookmarks are open then on the left hand side
>>> you'll see the svy manual.  After you've gone over the opening
>>> explanatory material, the section on svy estimation will highlight
>>> the many commands you have available.  You'll probably want commands
>>> like svy: tabulation, svy: mean, svy: regress, svy: logit, etc.
>>>
>>>

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