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Behavioural Surveillance Surveys - The Wisdom of Whores

Behavioural Surveillance Surveys - The Wisdom of Whores

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Notes:<br />

1. It may not always be possible to randomly<br />

select respondents in this fashion, but one<br />

should always try to find a way to get a<br />

headcount <strong>of</strong> target group members present<br />

at the site, and then systematically select<br />

the number that are needed. It is never<br />

advisable to take volunteers instead <strong>of</strong><br />

selecting respondents randomly.<br />

2. If fewer than the required number <strong>of</strong><br />

respondents (in this case 15) are present<br />

at the time <strong>of</strong> the survey team’s visit, then<br />

it will be necessary to return to the site at<br />

a later time to complete the cluster. If this<br />

cannot be done, then it will be necessary<br />

to record the number <strong>of</strong> respondents<br />

interviewed so that the second stage<br />

probability can be calculated at a later time.<br />

(See chapter 5 for instructions on how to<br />

calculate sampling probabilities and conduct<br />

weighted analysis). (Note : although<br />

returning to a site is sometimes necessary<br />

for this design, where conventional clusters<br />

are being used, it is not appropriate to<br />

return to a site when time-location clusters<br />

are being used).<br />

3. If, at the time <strong>of</strong> the team’s visit, it is<br />

discovered that the measure <strong>of</strong> size for<br />

the site that was estimated in the sampling<br />

frame is inaccurate, then it will be necessary<br />

to obtain an estimate <strong>of</strong> the number <strong>of</strong><br />

target group members who really are<br />

associated with the site, so that sampling<br />

probabilities can be calculated.<br />

Variation when measure <strong>of</strong> size for the cluster is<br />

not available ahead <strong>of</strong> time<br />

A variation on this design is one in which a<br />

measure <strong>of</strong> size is not available ahead <strong>of</strong> time,<br />

so it is not possible to select clusters by PPS.<br />

In this case, clusters will need to be selected<br />

with equal probability (see Figure 2 and Table<br />

3 from chapter 4), and it will be necessary to<br />

obtain an estimate <strong>of</strong> the number <strong>of</strong> people at<br />

the site on the day the data is collected, so<br />

that a first stage probability can be calculated.<br />

<strong>The</strong>re are two options for selecting respondents<br />

at the second stage. One option is to select<br />

the same number <strong>of</strong> respondents at each site.<br />

This makes the field work less complicated,<br />

but the resulting sample will not be selfweighted.<br />

So it will be necessary to calculate<br />

sampling probabilities, and perhaps conduct<br />

a weighted analysis. In order to avoid this,<br />

it is possible to decide on a sampling fraction<br />

ahead <strong>of</strong> time to be applied at each site. For<br />

example, it could be decided that at each site,<br />

25% <strong>of</strong> respondents found there would be<br />

interviewed. For example, if 80 people were<br />

found at a site, then 20 people (80/4=20)<br />

would be interviewed. And if 25 people were<br />

found at the site, then 6 people (25/4= 6.25)<br />

would be interviewed. This procedure is<br />

slightly more complicated and one issue is that<br />

you lose control over the total sample size.<br />

It is difficult to define what the sampling<br />

fraction should be, so that the final sample will<br />

not overshoot or undershoot the desired total<br />

sample size. However, the advantage <strong>of</strong> this<br />

approach, is that if it is done at every site, then<br />

the final sample is self-weighted. Whichever<br />

option is chosen, it is still necessary to obtain<br />

an estimate <strong>of</strong> the number <strong>of</strong> respondents<br />

at the site, so that sampling probabilities can<br />

be calculated.<br />

314<br />

A PPEN DI X 3 B EHAV I OR A L SURV EI L L A NC E S U R V EY S

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