Characterization and Diagnostic Tools for Factorial Block Designs R package FactChar version 1.0 Description: Provides comprehensive tools for analysing and characterizing mixed-level factorial designs arranged in blocks. Includes construction and validation of incidence structures, computation of C-matrices, evaluation of A-, D-, E-, and MV-efficiencies, checking of orthogonal factorial structure (OFS), diagnostics based on Hamming distance, discrepancy measures, B-criterion, Es^2 statistics, J2-distance and J2-efficiency, Phi-p optimality, and symmetry conditions for universal optimality. The methodological framework follows foundational work on factorial and mixed-level design assessment by Xu and Wu (2001) <doi:10.1214/aos/1013699993>, and Gupta (1983) <doi:10.1111/j.2517-6161.1983.tb01253.x>. These methods assist in selecting, comparing, and studying factorial block designs across a range of experimental situations. Software Imports: MASS, Matrix Sukanta Dash <sukanta.iasri@gmail.com> Comprehensive R Archive Network (CRAN) Sukanta Dash [aut, cre], Vankudoth Kumar [aut], Sunil Kumar Yadav [aut], Anil Kumar [aut], Med Ram Verma [aut] GPL-3 2025-12-12 application/tgz https://CRAN.R-project.org/package=FactChar doi:10.32614/CRAN.package.FactChar