Abstract:
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As a statistical collaborator at a medical center, you often encounter interesting projects that use both novel clinical approaches and offer an opportunity to use innovative statistical methods. The focus of this presentation is to provide a brief overview of a project from clinical microbiology. Current study builds on the prior research work that used Bayesian latent class models for estimation of sensitivity and specificity due to imperfect gold standard. Goal of this study is to assess number of specimens for each patient required for accurate diagnosis of a prosthetic joint infection (PJI). Findings of this study have direct impact on cost savings, timely and accurate diagnosis of infection.
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