Andrew Karl is a senior management consultant specializing in advanced analytical methods and JSL programming. He is an experienced R and JSL programmer. He has authored papers on a diverse set of topics, including scalable estimation of non-nested nonlinear mixed models, the impact of nonignorable missing data on models for teacher evaluation, bias in mixed model estimators, and parallel pseudorandom number generation. He received his Ph.D. in statistics from Arizona State University.
