[R] [non-statistics question]methodological problem
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 ). It is presumably less efficient
than using individual-level weights. A description from Statistics
Belgium is linked from ?calibrate.
 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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