Hello all
I have a question regarding how to weight a data set.
The data is from a population based cross sectional study.
5000 randomly selected men reflecting the backgound population were mailed a
questionaire.
75% responsrate. 3750 questionnaires filled out. We know the age and the zip
code for non-responders.
The questionnaire contained several sociodemographic parameters s1, s2,
..... Sn
Then 1845 men from the group that had filled out a questionnaire were
invited to take part in a scientific project. The men were randomly selected
with an equal number in each age group (15 age groups of one year
intervals). So 123 men in each group.
946 men accepted a telephone call. 768 men never responded and 131 refused
to be interwied on telephone.
864 men of the 946 were then randomly contacted with equal numbers in each
age group and 697 men agreed to take part in the project. 97 men later
cancelled or never showed up.
So 600 men were included for further studies.
Now I would like to weight these 600 men so they reflect the background
population in order to estimate the distribution of different measures in
the background population (X1, X2, .... Xi) based on measures amongst the
600 men (Y1, Y2, ..... Yi).
How do I do this?
As far as I can tell I need to compensate for the differences between the
5000 and the 3750 and between the 3750 and the 600. Since the 1845 were
randomly selected and an equal number in each age group were contacted I
assume that all men had an equal probability of being included so design
weights are not really needed. Right?
But how do I compute a pweight that takes the two steps into account?
I have looked a bit a the SURVWGT command in stata but I don't understand
it.
Could someone help me with some examples.
Thanks
Kristian
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