On the robustness of latent class models for diagnostic testing with no gold standard.

Journal Article (Journal Article)

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.

Full Text

Duke Authors

Cited Authors

  • Schofield, MR; Maze, MJ; Crump, JA; Rubach, MP; Galloway, R; Sharples, KJ

Published Date

  • May 14, 2021

Published In

PubMed ID

  • 33990992

Electronic International Standard Serial Number (EISSN)

  • 1097-0258

Digital Object Identifier (DOI)

  • 10.1002/sim.8999

Language

  • eng

Conference Location

  • England