I have a stratified data set that I want to calculate means and proportions
for using svymean and svyprop. Unfortunately I have some
strata with single PSU's and svymean and svyprop don't like this. The
manual and help service recommend 2 ways of dealing with the singleton
PSU's:
1. collapse across strata to effectively remove them (the advice being to
collapse in the way that makes most sense for your data)
2. drop the singleton PSU's
The preferred option for me is to collapse across strata and I can do this
easily enough. However I'm still not clear on the following:
1. do you need to recalculate probability weights?
2. Do you need to use the same collapsed strata for everyone? For example,
when I do svymean for Grade 9 boys I have 3 singelton PSU but when I do the
same analysis for Grade 10 boys there are 4 singleton PSU's, and at grade 11
7! The problem is much less in girls (grade 9 there is one, grade 10 1 and
grade11 3). Should I collapse to remove the singleton's at year 11 boys
(which would, by chance have the net effect of removing all the singletons
at all year/gender groups) calling the new strata NEWSTRA, and then use
NEWSTRA to define the data for all analyses, or should I be doing the
relevant collapse for each age/gender group?
Thanks for any help anyone can offer
Trish
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