Model | Additional data requirement | Assumptions related to detection |
---|---|---|
Standard logistic regression | None | Perfect detection (i.e., sensitivity and specificity equal to 100Â %) |
Bayesian model 1 | Estimate of sensitivity \(\widehat{SN}\) and specificity \(\widehat{SP}\) based on external study | Sensitivity and specificity are perfectly known constants, equal to the estimates from external study |
Bayesian model 2 | Data on sensitivity and specificity (i.e., \(N_{ + } ,T_{ + } ,N_{ - } ,T_{ - }\)) from external study | Sensitivity and specificity are constants and external study provides reasonable prior information on sensitivity and specificity for the target study |
Bayesian model 3 | Subset of individuals diagnosed with the regular and the gold standard method | Sensitivity and specificity can vary as a function of covariates. This model does not rely on data from external study (i.e., does not rely on transportability assumption) |