Implements methods for comparing sensitivities and specificities in balanced (or fully crossed) multi-reader multi-case (MRMC) studies with binary diagnostic test results. It implements conditional logistic regression and provides score tests equivalent to Cochran's Q test (which corresponds to McNemar's test when comparing two modalities only). The methodology is based on Lee et al. (2026) <doi:10.1002/sim.70471>.

Sample size estimations for MRMC studies based on the Obuchowski-Rockette (OR) methodology is implemented. The function can calculate sample sizes where the 
             endpoint of interest in the study is either ROC AUC (Area-Under-the-Receiver-Operating-Characteristics-Curve) or sensitivity. The package can also return sample sizes for studies
             expected to have clustering effect (e.g.- multiple pulmonary nodules per patient). All calculations assume that the study design is fully crossed (paired-reader, paired-case) where
             each reader reads/interprets each case and that there are two interventions/imaging-modalities/techniques in the study. In addition to MRMC, it can also be used to estimate sample sizes 
             for standalone studies where sensitivity or AUC are the primary endpoints.
             The methods implemented are based on the methods described in Zhou et.al. (2011) <doi:10.1002/9780470906514> and Obuchowski (2000) <doi:10.1097/EDE.0b013e3181a663cc>.

A causal mediation approach under the counterfactual framework 
    to test the significance of total, direct and indirect effects. In this approach, 
    a group of methylated sites from a predefined region are utilized as the mediator, 
    and the functional transformation is used to reduce the possible high dimension 
    in the region-based methylated sites and account for their location information.

Conduct multi-locus genome-wide association study under the framework of multi-locus random-SNP-effect mixed linear model (mrMLM). First, each marker on the genome is scanned. Bonferroni correction is replaced by a less stringent selection criterion for significant test. Then, all the markers that are potentially associated with the trait are included in a multi-locus genetic model, their effects are estimated by empirical Bayes, and all the nonzero effects were further identified by likelihood ratio test for significant QTL. The program may run on a desktop or laptop computers. If marker genotypes in association mapping population are almost homozygous, these methods in this software are very effective. If there are many heterozygous marker genotypes, the IIIVmrMLM software is recommended. Wen YJ, Zhang H, Ni YL, Huang B, Zhang J, Feng JY, Wang SB, Dunwell JM, Zhang YM, Wu R (2018, <doi:10.1093/bib/bbw145>), and Li M, Zhang YW, Zhang ZC, Xiang Y, Liu MH, Zhou YH, Zuo JF, Zhang HQ, Chen Y, Zhang YM (2022, <doi:10.1016/j.molp.2022.02.012>).