We explore the estimation of sensitivity and specificity of diagnostic tests when the true disease state is unknown. Instrumental variables which subdivide the patient population are used. A logistic model, relating these instrumental variables to the (unknown) true disease state is proposed. It is shown that this procedure allows the goodness-of-fit to the resulting model to be tested.
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