Sorry, you do not have access to this eBook
A subscription is required to access the full text content of this book.
Evaluation of sensitivity and specificity of diagnostic tests in the absence of a gold standard typically relies on latent structure models. For example, two extensions of latent class models in the biostatistics literature, Gaussian random effects (Qu et al., 1996) and finite mixture (Albert and Dodd, 2004), form the basis of several recent approaches to estimating sensitivity and specificity of diagnostic tests when no (or partial) gold standard evaluation is available. These models attempt to account for additional item dependencies that cannot be explained with traditional latent class models, where the classes typically correspond to healthy and diseased individuals.
A subscription is required to access the full text content of this book.
Other ways to access this content: