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Re: st: Survey question
From
Austin Nichols <[email protected]>
To
[email protected]
Subject
Re: st: Survey question
Date
Tue, 4 May 2010 13:49:39 -0400
Michael Norman Mitchell <[email protected]> :
Not if you stick with your SRS design--but there is a free lunch; if
you stratify you can reduce the variance, and if you stratify and use
unequal probabilities of selection, you can (with some luck or
foresight) reduce your variance substantially. What's the population?
Usually clustering will substantially reduce your costs and enable
you to get a bigger effective sample size, but that is not true of all
populations.
On Tue, May 4, 2010 at 1:37 PM, Michael Norman Mitchell
<[email protected]> wrote:
> Greetings
>
> I am embarrassed to ask this question, but I just want to be extra sure
> that I am on the right track.
>
> We have a sampling frame of people (a list of say 7000 people) and we are
> going to sample of say 300 of them. All people in the sampling frame will
> have an equal probability of being selected.
>
> Assume that we do not want to compute "totals" (i.e, counts, frequencies)
> in the population, and just focus on things like percentages, means, and
> estimation commands (like regress). In such a case, is there any need or
> benefit to calculate -pweights- and use the -svy- commands?
>
> Many thanks,
>
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