Diagnostic Test Accuracy Meta-Analysis using Template Model
Builder
dtametaTMB provides a unified framework for frequentist
meta-analysis of diagnostic test accuracy (DTA) studies in R. It
implements conventional gold-standard models, latent class extensions
for imperfect reference standards, subgroup analyses, and
multiple-threshold models within a consistent interface.
Key Features
Models
- Reitsma bivariate random-effects model
- Rutter and Gatsonis (HSROC) model
- Hoyer multiple-threshold model
- Latent class Reitsma and HSROC models for studies without a perfect
reference standard
Extensions
- Subgroup analyses
- HSROC meta-regression
- Parameter constraints for sparse-data settings
- Likelihood-ratio tests for nested model comparisons
Output
- Summary ROC (SROC/HSROC) plots
- Coupled forest plots
- RevMan-compatible exports
Implementation
- Frequentist estimation using exact binomial and multinomial
likelihoods
- Template Model Builder (TMB) backend
- Unified interface across model families
- Validation against published examples and Cochrane Handbook
analyses