ArticleStatistics in medicine2021
On the robustness of latent class models for diagnostic testing with no gold standard.
Article in Statistics in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Diagnosis of human leptospirosis: systematic review and meta-analysis of the diagnostic accuracy of the Leptospira microscopic agglutination test, PCR targeting Lfb1, and IgM ELISA to Leptospira fainei serovar Hurstbridge.BMC infectious diseases · 2024Pooled it
- A Dirichlet-Multinomial Gibbs Algorithm for Assessing the Accuracy of Binary Tests in the Absence of a Gold Standard.Statistics in medicine · 2026Article
- Proof-of-concept of bayesian latent class modelling usefulness for assessing diagnostic tests in absence of diagnostic standards in mental health.Scientific reports · 2025Article
- Article
- Bayesian Latent Class Models for Evaluating the Validity of Claim-based Definitions of Disease Outcomes.Annals of clinical epidemiology · 2024Article
- Simplifying the estimation of diagnostic testing accuracy over time for high specificity tests in the absence of a gold standard.Biometrics · 2023Article
- Estimating sensitivity and specificity of diagnostic tests using latent class models that account for conditional dependence between tests: a simulation study.BMC medical research methodology · 2023Article
- Bayesian latent class analysis produced diagnostic accuracy estimates that were more interpretable than composite reference standards for extrapulmonary tuberculosis tests.Diagnostic and prognostic research · 2022Article
- Role of Diagnostics in Epidemiology, Management, Surveillance, and Control of Leptospirosis.Pathogens (Basel, Switzerland) · 2022Review
- Rejoinder to "On the robustness of latent class models for diagnostic testing with no gold standard".Statistics in medicine · 2021Article
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6 authors.
Funding
Abstract
It is difficult to estimate sensitivity and specificity of diagnostic tests when there is no gold standard. Latent class models have been proposed as a potential solution as they provide estimates without the need for a gold standard. Using a motivating example of the evaluation of point of care tests for leptospirosis in Tanzania, we show how a realistic violation of assumptions underpinning the latent class model can lead directly to substantial bias in the estimates of the parameters of interest. In particular, we consider the robustness of estimates of sensitivity, specificity, and prevalence, to the presence of additional latent states when fitting a two-state latent class model. The violation is minor in the sense that it cannot be routinely detected with goodness-of-fit procedures, but is major with regard to the resulting bias.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.