The SCSmeta function implements the robust inverse variance heterogeneity (IVhet) model [1,2] for meta-analysis of diagnostic test accuracy studies. The SCS method starts off with the meta-analysis of the diagnostic odds ratios (DOR) and then splits the DOR into component measures (sensitivity, specificity, positive and negative likelihood ratio and AUC).
Upload your data to get results using the IVhet estimator. You need to provide a .csv file, organized in the format of this example . The columns to be analyzed must be named tp,fp,fn,tn (it doesn't matter if additional columns exist). Hope you find this useful!
[1]. Doi SA, Barendregt JJ, Khan S, Thalib L, Williams GM. Advances in the meta-analysis of heterogeneous clinical trials I: The inverse variance heterogeneity model. Contemp Clin Trials 2015; 45(Pt A):130-8.
[2]. Furuya-Kanamori L, Kostoulas P, Doi SA. A new method for synthesizing test accuracy data outperformed the bivariate method. J Clin Epidemiol. 2020.