Behavioural Surveillance Surveys - The Wisdom of Whores

...when measures of size are not available for
each PSU
If the number of individuals associated
with each “fixed” primary sampling unit is not
known (in other words where no measure of
size is available), it is obviously not possible
to select PSU with probability proportional
to their size. In this case, each PSU should
have an equal probability of being selected.
The procedures for choosing a sample of
clusters with equal probability are described
in Figure 2, and an example is provided in
Table 4. Form 2 in Appendix 4 can be used
in the field to assist with the selection of
clusters by equal probability.
If a fixed number of respondent group
members were to be chosen from each PSU
selected, this would lead to individuals having
differing overall probabilities of selection, and
the final sample would be non-self-weighting.
To continue the previous example, the
women in the brothel with 100 employees
would be less likely to be selected than the
women in the brothel with 50 employees.
Both brothels have the same probability of
selection into the sample, but because there
are twice as many women in the large
brothel, each woman is half as likely to end
up in the final sample. Since women in small
brothels might have different risk behavior
than women in big brothels, this unequal
probability of selection might bias the results
of the survey. To correct for this potential
bias, data can be weighted at the analysis
stage, as described in Chapter 5. Alternatively,
a fixed proportion (rather than a fixed number)
of individuals associated with each site could
be included in the survey — for example
every third group member. This would result
in a self-weighting sample. However it should
be noted that an estimated measure of size
will still be necessary at the time of data
collection if this method is to be used.
A drawback is that if the size of the population
associated with the PSU is not known
before-hand, using this second approach to
self-weighting will result in an unpredictable
final sample size.
Figure 2 : Steps in the selection of a systematic-random sample of primary
sampling units with equal probability
1. Prepare a numbered list of primary sampling units, preferably ordered geographically
(e.g., by areas of a city);
2. Calculate the sampling interval (SI) by dividing the total number of PSUs in the domain
(i.e. sub-population) (M) by the number of PSUs to be selected (a) — that is, SI = M/a;
3. Select a random number (RS) between 1 and (SI). The PSU on the numbered list
corresponding to this number will be the first sample unit;
4. Subsequent units are chosen by adding the sampling interval (SI) to the number identified
in step (3); that is RS + SI, RS + 2SI, RS + 3SI, etc;
5. This procedure is followed until the list has been exhausted.
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C H A PTER 4 B EHAV I OR A L S U R V EI L L A NC E S U R V EY S