Dear listers,
I have an opinion poll type dataset provided by a market research
company. It comes with a weight variable. I was told by their
representative that this weight variable is derived by something called
"rim weighting" which I am not familiar with from my medical stats
background.
From what I have mangaed to gather over the web, this type of weighting
is for handling any imbalance in a set of predetermined demographic
variables in an achieved sample (as compared with the target sample).
For example, one wanted to get 50 males and 50 females in their target
sample but ended up with 40 males and 60 females in their achieved
sample. From my limited understanding of rim weighting, one should then
give all of the males a weight of 1.25 and females 0.83. The specific
rim weights that comes with my dataset was created using the method
described above over a number of demographic variables, gender, age
groups (6 levels), social grade (6 grades), working status (working/no
working) and regions (11 regions), and then 'smoothed' to produce a
single weight. I was not told how the smoothing was done.
My question is whether I can treat this "rim weight" as sampling weight
as in most surveys.
My feeling is that I should not (use it as sampling weight) as it has
nothing to do with the probability of a person in the population being
selected in the sample - whose inverse is what sampling weight usually
is.
Any pointer or guidance will be very much appreciated. Many thanks in
advance.
Best wishes,
Edmond
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