Detecting departures from the conditional independence assumption in diagnostic latent class models: a simulation study.

ABSTRACT:

Background

Latent class models can be used to estimate diagnostic accuracy without a gold standard test. Early studies often assumed independence between tests given the true disease state, however this can lead to biased estimates when there are inter-test dependencies. Residual correlation plots and chi-squared statistics have been commonly utilized to assess the validity of the conditional independence assumption and, when it does not hold, identify which test pairs are conditionally dependent. We aimed to assess the performance of these tools with a simulation study covering a wide range of scenarios.

Methods

We generated data sets from a model with four tests and a dependence between tests 1 and 2 within the diseased group. We varied sample size, prevalence, covariance,

SUBMITTER: Okkaoglu Y 

PROVIDER: S-EPMC11619692 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature