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Support #723

Combining USOC/BHPS and zero weights

Added by David Hussey over 5 years ago. Updated about 3 years ago.

Status:
Resolved
Priority:
High
Assignee:
Category:
Weights
Start date:
02/14/2017
% Done:

100%


Description

I have a couple more very small queries following on from our analysis; these are mainly for re-assurance that we’ve done things correctly.

1) With regard to the Youth data, is it ok to combine BHPS and USOC? We couldn’t find a combined weight but assumed this was still ok given that it’s done for adults. Therefore, when I created my weights (for w2/4 and w2/6), I started off by combining the weights thus (after checking the overlap):

  • select cases with a non-zero weight for USOC or BGPS.
    sele if not (b_ythscus_xw =0 and b_ythscbh_xw =0).
  • calculate weight (wt) as either USOC weight or BHPS weight.
    compute wt=b_ythscus_xw.
    compute samptype=2.
    if wt=0 samptype=1.
    if wt=0 wt=b_ythscbh_xw.
    Val labels samptype 1 “BHPS” 2 “USOC”.

I then re-scaled the weights to average 1 within samptype and went on to model response to wave 4/6 contingent on wave 2, using interactions with samptype (USOC/BHPS) to take account of possible differences in response process between the two surveys. If it’s not ok to combine USOC and BHPS then my weights should still be fine given the way I’ve done them but it’d be helpful to know whether or not it’s ok to do so.

2) In the adult data, there seem to be many zero weights, more than we expected. We’d like to know if these are mainly related to students living in halls and other institutional addresses? E.g. among wave 5 fully productive interviews, the following syntax:

TEMP.
SELECT IF e_outcome = 11.
FRE e_indinub_xw.

yields 4,481 cases with 0 value for e_indinub_xw (cross-sectional adult main interview weight for USoc & BHPS samples).

Many thanks for your help.

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