[R] [non-statistics question]methodological problem

Thomas Lumley tlumley at u.washington.edu
Mon Oct 29 16:04:31 CET 2007

On Sat, 27 Oct 2007, eugen pircalabelu wrote:
> As mentioned in the subject, my question regards more the methodological 
> part that accompanies survey design and the statistical part that is 
> involved. So, I have the following data:

You might get more helpful (or more authoritative) advice on 
methodological issues in survey sampling on other lists, in particular 
from srmsnet, rather than posting the same question twice to r-help.

> Now, is there a possibility of designing some weights for each household 
> based on the characteristics of individuals which form the hh? Say, I 
> want to calibrate each hh for its occupational category but i don't have 
> the additional data for household, rather it is available for 
> individuals, ex: I don't know that 32% of households are included in the 
> category of studenthh (inclusion which is based on the status of the 
> head of hh), but i know that 32% of all the individuals from which the 
> sample of hhs is drawn are all students.

Yes and no.  You can't calibrate to population totals you don't know.

You can create household-level weights that calibrate the individual-level 
data to individual-level population totals. And the survey() package knows 
how to do this: it is the aggregate.stage= or aggregate.index= argument to 
calibrate(), depending on whether you are using replicate weights or 
design information for your standard errors.

I don't know if this technique is useful in your setting.  My impression 
is that it is mainly used by national statistics agencies that want to 
avoid weird-looking inconsistencies (eg 2,000,000 marriages involving 
1,100,000 men and 900,000 women [1]).  It is presumably less efficient 
than using individual-level weights.  A description from Statistics 
Belgium is linked from ?calibrate.


[1] Apart from in civilised places like, eg, Canada or MA.

Thomas Lumley			Assoc. Professor, Biostatistics
tlumley at u.washington.edu	University of Washington, Seattle

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