Threshold Modeling
Cross-source consensus on Threshold Modeling from 1 sources and 4 claims.
1 sources · 4 claims
How it works
Benefits
Highlighted claims
- The latent transformed test result is assumed to follow a logistic distribution. — Meta-analysis of networks of diagnostic tests with binary and continuous results
- The model uses a parametric logistic relationship between threshold and the probability of testing positive within each disease class. — Meta-analysis of networks of diagnostic tests with binary and continuous results
- The threshold model avoids choosing a single threshold per study or per test. — Meta-analysis of networks of diagnostic tests with binary and continuous results
- Reparameterization around the most commonly reported threshold makes the model compatible with standard bivariate DTA meta-analysis at that threshold. — Meta-analysis of networks of diagnostic tests with binary and continuous results