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From |
Philip Burgess <philip.burgess.uq@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Postestimation puzzle(s) |

Date |
Wed, 25 Nov 2009 15:31:19 +1000 |

Sorry about this - I made an error with my cutting & pasting so some of the details were incorrect in the initial posting. This is a replacement. Apologies; Philip **************** Hi; I have 2 surveys, 1997 & 2007, with complex survey designs and available for analysis with Jackknife replicate weights. The surveys were more or less equivalent in their design: nationally representative random (independent) samples (without replacement). A possible issue is that the 1997 survey included persons aged 18 years or older (no upper limit); the 2007 survey included persons aged 16 – 85 years inclusive. As such, there could be issues about combining the two surveys given that the replicate weights are calibrated to different population structures – not sure there is any way around this if this is an explanation. I want to age-sex standardize the 1997 data to the 2007 population structure. To do so, I first limited the two samples to respondents aged 20-69 years inclusive – to get like-with-like comparisons. I then created a new variable indicating the age-sex strata (10 5-year age bands x 2 sex = 20 strata – variable name, st_agesex). I then estimated the 2007 population size for each of these 20 age-sex strata – variable name, st_wt). I do several runs through the data. The first specifies the complex survey design: . quietly svyset [pweight=mhsfinwt], jkrweight(wpm*, multiplier(1)) vce(jackknife) mse Stata output reports: Number of strata = 1; Population size = 1.39 million. All this makes sense. I then estimate proportions who consulted a psychologist for mental health problems in the last 12-months (mhpsyco12: code 0/1) over the two surveys (nsmhwb, 0 = 1997; 1 = 2007) . svy jackknife, nodots : proportion mhpsyo12, over(nsmhwb) These give estimates for the unadjusted populations: 1997 - 17.0% (SE 1.3%); 2007 – 37.3% (SE 2.5%). All good so far. The second pass through the data declares the complex survey design with poststratification specification strata and weights: . quietly svyset [pweight=mhsfinwt], poststrata(st_agesex) postweight(st_wt) /// jkrweight(wpm*, multiplier(1)) vce(jackknife) mse Stata output reports Number of strata = 1; N. of poststrata = 20, and Stata also reports a Population size of 1. I don’t understand the Population size parameter – why isn’t it 1.39 mill per above? I then estimate proportions who consulted a psychologist for mental health problems in the last 12-months adjusted for the age-sex stratum factors . svy jackknife, nodots : proportion mhpsyo12, over(nsmhwb) These give estimates for the ‘adjusted’ age-sex standardized populations: 1997 - 15.7% (SE 1.4%); 2007 – 37.1% (SE 2.6%). I expected the 1997 estimate to be reduced given age-sex adjustment – this is the case. But I do not understand why the 2007 ‘adjusted’ estimates vary at all from the 2007 ‘unadjusted’ unadjusted estimates. Finally, to try and unravel this matter, I resorted to the original complex survey design declaration: . quietly svyset [pweight=mhsfinwt], jkrweight(wpm*, multiplier(1)) vce(jackknife) mse Stata output reports Number of strata = 1; N. of std strata = 20 – both of these make sense. Stata also reports a Population size of 1.39 million. All of these make sense. I then tried to ‘directly standardize’ the proportions: . svy jackknife, nodots : proportion mhpsyo12, stdize(st_agesex) stdweight(st_wt) over(nsmhwb) These give estimates for the ‘adjusted’ age-sex standardized populations: 1997 - 15.6% (SE 1.4%); 2007 – 37.8% (SE 3.0%). So, I’m confused. I understand why the 1997 estimates vary given age-sex adjustment (although a bit confused why the results differ between poststratification and direct standardization); I have more trouble understanding the varying estimates for 2007. I’m struggling to understand all of this and welcome any ideas! It’s likely I do not properly understand the postsratification processes. I’m using Stata 11.0, born 21 October 2009. Any thoughts or ideas most grateful! Thanks; Philip. * * 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: Postestimation puzzle(s)***From:*Philip Burgess <philip.burgess.uq@gmail.com>

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