Commentary on ``On the robustness of latent class models for diagnostic testing with no gold-standard by Schofield et al.

Cites Work

On model expansion, model contraction, identifiability and prior information: two illustrative scenarios involving mismeasured variables
When Do Latent Class Models Overstate Accuracy for Diagnostic and Other Classifiers in the Absence of a Gold Standard?
Multiple-Bias Modelling for Analysis of Observational Data
A Cautionary Note on the Robustness of Latent Class Models for Estimating Diagnostic Error without a Gold Standard
Insights into latent class analysis of diagnostic test performance
Random Effects Models in Latent Class Analysis for Evaluating Accuracy of Diagnostic Tests
On the robustness of latent class models for diagnostic testing with no gold standard

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