'Shiny' Application to visualize Olympic Data. From 1896 to
    2016. Even Winter Olympics events are included. Data is from Kaggle at
    <https://www.kaggle.com/heesoo37/120-years-of-olympic-history-athletes-and-results>.

It is a computer tool to estimate the item-sum score's reliability (composite reliability, CR) in multidimensional scales with overlapping items. An item that measures more than one domain construct is called an overlapping item. 
    The estimation is based on factor models allowing unlimited cross-factor loadings such as exploratory structural equation modeling (ESEM) and Bayesian structural equation modeling (BSEM). The factor models include correlated-factor models and bi-factor models. Specifically for bi-factor models, a type of hierarchical factor model, the package estimates the CR hierarchical subscale/hierarchy and CR subscale/scale total. The CR estimator 'Omega-generic' was proposed by Mai, Srivastava, and Krull (2021) <https://whova.com/embedded/subsession/enars_202103/1450751/1452993/>. The current version can only handle continuous data. 
    Yujiao Mai contributes to the algorithms, R programming, and application example. Deo Kumar Srivastava contributes to the algorithms and the application example. Kevin R. Krull contributes to the application example. The package 'OmegaG' was sponsored by American Lebanese Syrian Associated Charities (ALSAC). However, the contents of 'OmegaG' do not necessarily represent the policy of the ALSAC.

A generalised data structure for fast and efficient loading and data munching of sparse omics data. The 'OmicFlow' requires an up-front validated metadata template from the user,
    which serves as a guide to connect all the pieces together by aligning them into a single object that is defined as an 'omics' class. 
    Once this unified structure is established, users can perform manual subsetting, visualisation, and statistical analysis, or leverage the automated 'autoFlow' method to generate a comprehensive report.