Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org.

[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

From |
Steven Samuels <sjsamuels@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Sample weights: Combining strata estimates to get one overall estimate |

Date |
Fri, 8 Apr 2011 10:38:13 -0400 |

Rahul, Just -svyset- your data with the poststrata() and postweight() options. The following code illustrates this and shows how to do it by hand. **********CODE BEGINS********* sysuse auto, clear gen postwx=2000 if foreign==0 //total pop for Domestic replace postwx= 1000 if foreign==1 //total pop for Foreign svyset _n [pw=turn], strata(foreign) svy: tab foreign, count // sum of weights: 2155 for Domestic 779 Foreign svyset _n [pw=turn], strata(foreign) poststrata(foreign) postweight(postwx) svy: tab foreign, count // Post-stratification "by hand": gen new_wt= (2000/2155)*turn if foreign==0 replace new_wt =(1000/779)*turn if foreign==1 svyset _n [pw=new_wt], strata(foreign) svy: tab foreign, count **********CODE ENDS********* The totals used (2000, 1000 here) need not be actual totals, but numbers that are close and maintain the correct proportions. In analysis of 2005-2006 data from India, for example, I used totals from the 2001 Census of India. Disproportionate stratum sample sizes by themselves will not cause problems. In a survey that samples all stages with PPS, the sum of weights in a stratum is an independent estimate of the stratum's population size. For a good reference on weighting, see Chapter 8 of Sharon Lohr 2009. Sampling: Design and Analysis. Pacific Grove, CA: Brooks Cole Publishing Company. After you have looked at that, I encourage you to "rake" (post-stratify simultaneously) other factors, such as urban/rural totals, age/gender totals, village size. In Stata you can do this with -survwgt rake-, contained in Nick Winter's -svr- package at SSC. Steve Steven J. Samuels Consulting Statistician 18 Cantine's Island Saugerties, NY 12477 USA Voice: 845-246-0774 Fax: 206-202-4783 sjsamuels@gmail.com On Apr 7, 2011, at 12:09 PM, Rahul wrote: Dear Statalist, I had a weighting related question. I am developing weights for household sample survey in State of Karnataka in India. In our sampling design we divide the state into four strata (regions) and > pick districts (biggest sampling unit within the region) within the stratas > randomly. Then we divide each district into rural and urban strata. We do > random sampling using Population proportion to size sampling at stages below > this in picking taluks (biggest administrative unit in a district) and then > villages (our FSU's). > > We have developed weights for each region [which are all inverse > of probability of selection at each stage of sampling] separately. So we get > weighted rural estimate for Region 1,2,3 and 4. We need to combine these > four estimates to get an estimate at the rural state level. > > The stratification is disproportionate i.e. each strata's sample size is > not exactly proportional to its share in the overall population of the > state. In some strata the proportion of sample of > the overall state sample is greater than its corresponding proportion > of strata population to the total population. These are off by a few > percentage points. We are assuming if they were similar we needn't make any > adjustment and the State overall estimate is just simple combination of each > strata's estimate. > > How should we combine the strata estimates? Do we need to make > the correction for disproportionate ?. Is it needed and in what form?. Can > we just multiply the correction term with the probability weight which we > are providing stata? > > the step above would give me two estimates rural and urban estimates at > the state level. rural/urban is also a strata. To combine this and get > one estimate at the state level do we have to multiply by some factor?. > > In short, our question is how to combine strata level estimates to get > one overall estimate - especially in case where we have disproportionate > stratification. > > I would appreciate any help in this regards. > > thanks > rahul > * * * 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/

**References**:**st: Sample weights: Combining strata estimates to get one overall estimate***From:*Rahul <rahul.lahoti@gmail.com>

- Prev by Date:
**st: Kernel methods / machine learning** - Next by Date:
**st: Average Rolling Regression Coefficient Significance** - Previous by thread:
**st: Sample weights: Combining strata estimates to get one overall estimate** - Next by thread:
**st: Rivtest p-values** - Index(es):