Behavioural Surveillance Surveys - The Wisdom of Whores

Figure 6 : Procedures for calculating sampling probabilities for sample elements
(P i
) chosen using the various prototype sub-population survey sample designs
(continued)
5. Selection of schools PPS, classes with
equal probability, and all students in
sample classes chosen for sample
P ij
= (m * M i
/M) * (b/B i
)
Where:
P ij
= probability that a sub-population member
in class j of school i was chosen for the
survey;
m = number of sample schools chosen;
M i
= measure of size for school i;
M = total measure of size for schools in the
survey universe (M = ΣMi);
b = number of classes chosen for the sample;
and
B i
= total number of classes in sample school i.
Note: This design results in a non-self-weighting
sample, and it will thus be necessary to apply sampling
weights during analysis.
6. Selection of schools PPS and students
sub-sampled at randomly chosen
interview sites
P ij
= (m * M i
/M) * n i
/N i
Where:
P ij
= probability that a sub-population member
in class j of school i was chosen for the
survey;
m = number of sample schools chosen;
M i
= measure of size for school i;
M = total measure of size for schools in the
survey universe (M = ΣMi);
n i
= number of sub-population members
chosen in cluster i; and
N i
= total number of sub-population
members in the cluster i.
7. Household surveys of youth, clusters
chosen with PPS, constant number of
youth chosen per cluster at second stage
using segmentation method:
P i
= (m * M i
/M) * 1/S i
= m * C/M
Where:
M = number of sample clusters chosen;
M i
= measure of size for the ith cluster;
M = total measure of size for the survey
universe (M = ΣMi);
S i
= number of segments created in the ith
cluster; and
C = standard (i.e., constant) segment size.
Note: Since this design results in a self-weighting
sample, the application of sampling weights during
analysis is not required.
8. Household surveys of youth, clusters
chosen with PPS, constant number of
youth chosen per cluster at second stage
using a random walk method:
P I
= (m * M i
/M) * k/N i
Where:
M = number of sample clusters chosen;
M i
= measure of size for the ith cluster;
M = total measure of size for the survey
universe (M = ΣMi);
k = constant number of households chosen
per cluster; and
N i
= total number of households in the ith
cluster.
Note: This design results in a non-self-weighting sample,
and it will thus be necessary to apply sampling weights
during analysis.
Note: This design results in a non-self-weighting
sample, and it will thus be necessary to apply sampling
weights during analysis.
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C H A PTER 5 B EHAV I OR A L S U R V EI L L A NC E S U R V EY S