Inference of diagnostic characteristics without a gold standard for disease classification | Institute for Risk and Uncertainty

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Alex Winbush:
Inference of diagnostic characteristics without a gold standard for disease classification

This presentation introduces a means of inferring diagnostic test statistics without a 'gold-standard' second test through possibility theory (end even without any second test at all). Precise, or imprecise, knowledge about the correlation between test results, population prevalence, and even the statistics of the comparison test can all help to improve the answer but are optional. You can even infer them as well if you have enough data!

Alex Wimbush is a PhD student at the Institute for Risk and Uncertainty, University of Liverpool, and is currently writing his thesis on optimising combinations of diagnostic tests under uncertainty. His work centres around confidence based methods of inference, prediction, and calculation using possibility theory and c-boxes.

Alex Winbush: Inference of diagnostic characteristics without a gold standard for disease classification

Alex Winbush:
Inference of diagnostic characteristics without a gold standard for disease classification