Ph.D., Florida State University, 1990
MBA, Florida State University, 1986
BBA, Florida Atlantic University, 1985
A.A., Broward Community College, 1982
Dr. Brusco’s current research focuses on clustering, network analysis, and variable/feature selection in the psychological and behavioral sciences.
Brusco, M. (2019). An Excel spreadsheet and VBA macro for model selection and predictor importance using all-possible-subsets regression. Spreadsheets in Education, 12 (1), Retrieved from: https://sie.scholasticahq.com/article/8064-an-excel-spreadsheet-and-vba-macro-for-model-selection-and-predictor-importance-using-all-possible-subsets-regression
Brusco, M. (2018). Demonstrating the mechanics of principal component analysis via spreadsheets. Spreadsheets in Education, 11 (1), Retrieved from: https://sie.scholasticahq.com/article/6895-demonstrating-the-mechanics-of-principal-component-analysis-via-spreadsheets
Brusco, M. J., & Doreian, P. (2019). Partitioning signed networks using relocation heuristics, tabu search, and variable neighborhood search. Social Networks, 56 (January), 70-80.
Brusco, M. J., Voorhees, C. M., Calantone, R. J., Brady, M. K., & Steinley, D. (2019). Integrating linear discriminant analysis, polynomial basis expansion, and genetic search for two-group classification. Communications in Statistics – Simulation and Computation, 48 (6), 1623-1636.
Brusco, M. J., Steinley, D., Stevens, J., & Cradit, J. D. (2019). Affinity propagation: an exemplar-based tool for clustering in psychological research. British Journal of Mathematical and Statistical Psychology, 72 (1), 155-182.
Brusco, M. J., Cradit, J. D., & Steinley, D. (in press). Combining diversity and dispersion criteria for anticlustering: a bicriterion approach. British Journal of Mathematical and Statistical Psychology.
Brusco, M. J., Steinley, D., & Stevens, J. (in press). K-medoids inverse regression. Communications in Statistics – Theory and Methods.
Brusco, M. J., Cradit, J. D., & Brudvig, S. (in press). An integrated dominance analysis and dynamic programming approach for measuring predictor importance for customer satisfaction. Communications in Statistics – Theory and Methods.
Brusco, M. J., Steinley, D., & Köhn, H.-F. (in press). Residual analysis for unidimensional scaling in the L2-norm. Communications in Statistics – Simulation and Computation.
Brusco, M. J., Johns, T. R., & Venkataraman, R. (2018). LP-based working subsets for personnel scheduling: evaluation and augmentation. European Journal of Industrial Engineering, 12 (2), 175-198