Abstract:
:In this work, we describe a two-stage sampling design to estimate the infection prevalence in a population. In the first stage, an imperfect diagnostic test was performed on a random sample of the population. In the second stage, a different imperfect test was performed in a stratified random sample of the first sample. To estimate infection prevalence, we assumed conditional independence between the diagnostic tests and develop method of moments estimators based on expectations of the proportions of people with positive and negative results on both tests that are functions of the tests' sensitivity, specificity, and the infection prevalence. A closed-form solution of the estimating equations was obtained assuming a specificity of 100% for both tests. We applied our method to estimate the infection prevalence of visceral leishmaniasis according to two quantitative polymerase chain reaction tests performed on blood samples taken from 4756 patients in northern Ethiopia. The sensitivities of the tests were also estimated, as well as the standard errors of all estimates, using a parametric bootstrap. We also examined the impact of departures from our assumptions of 100% specificity and conditional independence on the estimated prevalence.
journal_name
Stat Medjournal_title
Statistics in medicineauthors
Miller E,Huppert A,Novikov I,Warburg A,Hailu A,Abbasi I,Freedman LSdoi
10.1002/sim.6545subject
Has Abstractpub_date
2015-11-10 00:00:00pages
3349-61issue
25eissn
0277-6715issn
1097-0258journal_volume
34pub_type
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