RE: st: using post stratification weights

[Cameron McIntosh <cnm100@hotmail.com>]

Afif,
These will likely make things more clear:
Gelman, A., & Carlin, J.B. (2002). Poststratification and weighting adjustments. In R.M. Groves, D.A. Dillman, J.L. Eltinge & R.J.A. Little (Eds.), Survey Nonresponse (pp. 289–302). New York, NY: Wiley.

Gelman, A. (2007). Struggles with Survey Weighting and Regression Modeling. Statistical Science, 22(2), 153-164.http://projecteuclid.org/DPubS/Repository/1.0/Disseminate?view=body&id=pdfview_1&handle=euclid.ss/1190905511

Little, R.J.A. (1993). Post-stratification: A modeler’s perspective. Journal of the American Statistical Association, 88, 1001–1012.

Lazzeroni, L.C. and Little, R.J.A. (1998). Random-effects models for smoothing poststratification weights. Journal of Official Statistics, 14, 61–78.

Holt, D., & Mith, T.M.F. (1979). Post stratification. Journal of the Royal Statistical Society, Series A, 142, 33–46.

Cam
----------------------------------------
> From: afeef745@hotmail.com
> To: statalist@hsphsun2.harvard.edu
> Subject: st: using post stratification weights
> Date: Fri, 10 Feb 2012 20:31:56 -0500
>
> I am working with a data set with post-stratification weights generated by =
> the firm that conducted the survey. My sample shows some deviation from the=
> population summary statistics=2C so I would like to use post-stratificatio=
> n weights in Logit model. I have been trying to figure out myself for a cou=
> ple of days how to do it=2C but havent made much progress in this regard. S=
> o decided to seek some help here.
>
> The post-stratification weights are generated through iterative proportiona=
> l fitting. Quote from the survey hand-book itself is below:
>
> "The following benchmark distributions are utilized for this post-stratific=
> ation adjustment:
> Gender (Male=2C Female)
> Age (18-29=2C 30-44=2C 45-59=2C 60+)
> Race/Hispanic ethnicity
> Education category
> Metropolitan Area (Yes=2C No)
> Internet Access (Yes=2C No)
>
> Comparable distributions are calculated using all completed cases from the =
> field data. Since
> study sample sizes are typically too small to accommodate a complete cross-=
> tabulation of all the
> survey variables with the benchmark variables=2C an iterative proportional =
> fitting is used for the
> post-stratification weighting adjustment. This procedure adjusts the sample=
> data back to the
> selected benchmark proportions. Through an iterative convergence process=2C=
> the weighted
> sample data are optimally fitted to the marginal distributions."
>
> I have been looking at the STATA survey command to figure it out myself. Bu=
> t havent made much progress. I would really appreciate if someone can help =
> me out here.
>
> Regards
> Afif
>
>
>
>
>
>
>
>
>
>
>
>
>
> text here
>
> *
> * For searches and help try:
> * http://www.stata.com/help.cgi?search
> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
 		 	   		  

*
*   For searches and help try:
*   http://www.stata.com/help.cgi?search
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/