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2005
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20 Nov 2005

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METHODOLOGY
Kumar R, Indrayan A. A nomogram for singlestage clustersample surveys in a
community for estimation of a prevalence rate. Int J Epidemiol 31(2):4637,
2002.
Abstract: BACKGROUND: Proper assessment
of the magnitude of the problem is essential for devising adequate allocation of
available resources and for developing future strategies to combat a disease.
The cluster random sampling (CRS) technique is commonly used for rapid
assessment of public health problems in developing countries. Our objective is
to devise a nomogram that can instantly provide the number of clusters of
specified size needed to estimate the prevalence rate of a disease in a
community with given precision, ratio of designeffect to cluster size and
confidence level. This would be applicable only to singlestage CRS. METHODS: We
use a logarithmic transformation to linearize the relation between the number of
clusters (C) on one side and designeffect (D), cluster size (B), precision (L),
anticipated prevalence rate (P) and confidence level (alpha) on the other. By
using this relation, we construct a nomogram using established methods. RESULTS:
A nomogram is obtained that can be used to determine the number of clusters
needed in a survey with the help of only a ruler when other parameters are
known. This is a 6in1 figure as it gives the number of clusters C
corresponding to any combination of alpha from among the popularly used 0.05,
0.10 and 0.20, and precision 10% of P or 20% of P. Using a very simple
calculation, the number of clusters for the other values of alpha and L can also
be obtained. CONCLUSION: This nomogram can be a useful aid in instantly
providing the number of clusters required to rapidly estimate the prevalence
rate of a disease in a community when the ratio of designeffect to cluster
size, confidence level, and precision are specified. However, it is not
applicable to intervention studies where interest mainly focuses on testing a
hypothesis rather than estimation.
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