The design effect and cluster samples: optimising tuberculosis prevalence surveys [Educational series: prevalence surveys. Serialised guidelines. Assessing tuberculosis prevalence through population-based surveys. Number 2 in the series]
Abstract:Cross-sectional surveys of disease prevalence, including for tuberculosis (TB), often use a two (or more) stage sampling procedure. By choosing clusters of people randomly from all possible clusters, the logistic costs of doing the survey can be reduced. However, this increases the statistical uncertainty in the estimate of prevalence, and we need to balance the reduction in cost against the increase in uncertainty. Here we describe cluster sampling and consider ways to determine the optimal survey design as well as the extent to which deviations from the optimal design matter. We illustrate the results using data from a recent survey in Cambodia in which TB was diagnosed using sputum smears, cultures and X-rays.
Document Type: Invited Paper
Affiliations: 1: World Health Organization, Geneva, Switzerland 2: TB Research Centre, Chennai, India 3: KNCV Tuberculosis Foundation, The Hague, The Netherlands 4: Research Institute of Tuberculosis, Japan Anti-Tuberculosis Association, Tokyo, Japan
Publication date: 2008-10-01
The International Journal of Tuberculosis and Lung Disease publishes articles on all aspects of lung health, including public health-related issues such as training programmes, cost-benefit analysis, legislation, epidemiology, intervention studies and health systems research. The IJTLD is dedicated to the continuing education of physicians and health personnel and the dissemination of information on tuberculosis and lung health world-wide.
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