R McNamee1. 1. Biostatistics Group, School of Epidemiology and Health Sciences, University of Manchester, Oxford Road, Manchester M13 9PT, UK. rmcnamee@man.ac.uk
Abstract
BACKGROUND: Unbiased estimation of the prevalence of diseases and other conditions is important but can be expensive, especially for conditions which do not necessarily lead to contact with health services. A two-phase population survey may seem an attractive option when there is a relatively cheap, although fallible, test for disease status available: the test is used in the first phase of the survey but in the second, only a subsample are classified by the relatively expensive, gold standard. Previously the cost efficiency of such studies compared with simple, one-phase random sample designs was investigated empirically and some questions remain unclear. METHODS: A simple formula for the maximum reduction in cost or standard error that can be achieved by two-phase sampling compared with simple random sampling is derived mathematically. A formula for the minimum reduction is also given and the influence of prevalence on efficiency explained. RESULTS: The main result shows that the sensitivity and specificity of the first stage test set an absolute limit on the efficiency of two-phase designs; in particular, two-phase sampling can never be justified on efficiency grounds alone if the test is not accurate enough.
BACKGROUND: Unbiased estimation of the prevalence of diseases and other conditions is important but can be expensive, especially for conditions which do not necessarily lead to contact with health services. A two-phase population survey may seem an attractive option when there is a relatively cheap, although fallible, test for disease status available: the test is used in the first phase of the survey but in the second, only a subsample are classified by the relatively expensive, gold standard. Previously the cost efficiency of such studies compared with simple, one-phase random sample designs was investigated empirically and some questions remain unclear. METHODS: A simple formula for the maximum reduction in cost or standard error that can be achieved by two-phase sampling compared with simple random sampling is derived mathematically. A formula for the minimum reduction is also given and the influence of prevalence on efficiency explained. RESULTS: The main result shows that the sensitivity and specificity of the first stage test set an absolute limit on the efficiency of two-phase designs; in particular, two-phase sampling can never be justified on efficiency grounds alone if the test is not accurate enough.
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