  Objectives: This study provides an effective model selection method based on
the empirical likelihood approach for constructing summary receiver operating
characteristic (sROC) curves from meta-analyses of diagnostic studies.
  Methods: We considered models from combinations of family indices and
specific pairs of transformations, which cover several widely used methods for
bivariate summary of sensitivity and specificity. Then a final model was
selected using the proposed empirical likelihood method. Simulation scenarios
were conducted based on different number of studies and different population
distributions for the disease and non-disease cases. The performance of our
proposal and other model selection criteria was also compared.
  Results: Although parametric likelihood-based methods are often applied in
practice due to its asymptotic property, they fail to consistently choose
appropriate models for summary under the limited number of studies. For these
situations, our proposed method almost always performs better.
  Conclusion: When the number of studies is as small as 10 or 5, we recommend
choosing a summary model via the proposed empirical likelihood method.
