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Anita Israni is an Assistant Professor in the Department of Educational Psychology at the University of Texas at Austin. Her research primarily focuses on hierarchical linear modeling, particularly on longitudinal mediation data. Israni is dedicated to extending basic multilevel models to incorporate the complexities of data structures, as well as cross-classified multiple membership structures found in empirical data. She also addresses measurement errors to enhance the reliability and accuracy of parameter estimates. With a background in software development, Israni has experience in Unix/Linux, C++, and R, using Bayesian methods in her research, along with specialized software programs such as WinBUGS, OpenBUGS, and Rstan. She utilizes the supercomputer at the University of Texas at Austin for various simulation analyses. In addition to her research, Israni teaches both undergraduate and graduate statistics courses. She has co-authored a chapter on modeling interrelated student and teacher test score data using a cross-classified model, and possesses extensive experience in the private education sector, focusing on administration, management, and teaching a variety of mathematical and technical courses including Calculus, Differential Equations, Engineering Economics, and Probability & Statistics.
General requirements for the Graduate School at UT Austin apply to all programs unless otherwise specified.