diagnostic test evaluation 1directed acyclic graphs 1latent class analysis 1measurement error 1model identifiability 1
From the 1 of 3 linked papers with an AI index.
3 papers
stat.ME2026
Improving interpretation of latent class models for diagnostic tests by recognizing their measurands via directed acyclic graphs (DAGs)
Nandini Dendukuri, Ian Schiller, Else Bijker +4
The paper shows how using directed acyclic graphs (DAGs) to represent the measurands of imperfect diagnostic tests can improve latent class models, leading to more accurate estimat…
stat.ME2026
Using Directed Acyclic Graphs to Illustrate Common Biases in Diagnostic Test Accuracy Studies
Yang Lu, Nandini Dendukuri
Background: Diagnostic test accuracy (DTA) studies, like etiological studies, are susceptible to various biases including reference standard error bias, partial verification bias,…
stat.ME2025
Examining the Association between Estimated Prevalence and Diagnostic Test Accuracy using Directed Acyclic Graphs
Yang Lu, Robert Platt, Nandini Dendukuri
There have been reports of correlation between estimates of prevalence and test accuracy across studies included in diagnostic meta-analyses. It has been hypothesized that this une…