Bridging Log-Odds Ratios and Correspondence Analysis via Closeness-of-Concordance Measures // Provides a unified analytical workflow that bridges conventional binary and multinomial logistic regression with singly-ordered (SONSCA) and doubly-ordered (DONSCA) nonsymmetric correspondence analysis. Log-odds ratios (LORs) from logistic regression are re-expressed as cosine theta estimates and closeness-of- concordance measures (CCMs) -- including Yule's Q, Yule's Y, and r_meta -- on the familiar [-1, +1] scale introduced by Kim and Grochowalski (2019) doi:10.1007/s00357-018-9277-7. Bootstrap confidence intervals for cosine theta are provided throughout. The package is intended to help clinical and medical researchers interpret association strength from logistic regression in an intuitive, correlation-like metric, and to connect conventional regression results with geometric correspondence analysis visualisations.