Teresa Gibson Headshot

Teresa Gibson

Professor of Practice

School of Mathematics and Statistics
College of Science

585-475-5387
Office Location

Teresa Gibson

Professor of Practice

School of Mathematics and Statistics
College of Science

585-475-5387

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Journal Paper
Gibson, Teresa B. "A Dynamic Analysis of Medication Adherence." The Journal of Managed Care & Specialty Pharmacy 28. 12 (2022): 1392-1399. Print.
Haff, Nancy, et al. "Association Between Cost-Saving Prescription Policy Changes and Adherence to Chronic Disease Medications: an Observational Study." Journal of General Internal Medicine 37. (2022): 531-538. Print.
Thornhill, Martin H, et al. "Antibiotic Prophylaxis Against Infective Endocarditis Before Invasive Dental Procedures." Journal of the American College of Cardiology 11. (2022): 1029-1041. Print.
Livingston, Nicholas A, et al. "The Impact of COVID-19 and Rapid Policy Exemptions Expanding on Access to Medication for Opioid Use Disorder (MOUD): A Nationwide Veterans Health Administration Cohort Study." Drug Alcohol Depend 241. (2022): 109678. Web.

Currently Teaching

STAT-500
3 Credits
This course introduces the student to statistical situations not encountered in regular course of study. It integrates and synthesizes concepts in statistical theory with applications. Topics include open-ended analysis of data, current techniques and practice of statistics, development of statistical communication skills and the use of statistical software tools in data analysis. Each student is required to learn and use a statistical technique beyond what is covered in the previous courses. Students are expected to introduce the method in a presentation and to prepare a comprehensive, professional report detailing the statistical method and its application to a data set.
STAT-511
3 Credits
This course is an introduction to the statistical-software package R, which is often used in professional practice. Some comparisons with other statistical-software packages will also be made. Topics include: data structures; reading and writing data; data manipulation, subsetting, reshaping, sorting, and merging; conditional execution and looping; built-in functions; creation of new functions; graphics; matrices and arrays; simulations and app development with Shiny.
STAT-611
3 Credits
This course is an introduction to the statistical-software package R, which is often used in professional practice. Some comparisons with other statistical-software packages will also be made. Topics include: data structures; reading and writing data; data manipulation, subsetting, reshaping, sorting, and merging; conditional execution and looping; built-in functions; creation of new functions; graphics; matrices and arrays; simulations and app development with Shiny.
STAT-775
3 Credits
This is a graduate level survey course that stresses the concepts of statistical design and analysis for clinical trials. Topics include the design, implementation, and analysis of trials, including treatment allocation and randomization, factorial designs, cross-over designs, sample size and power, reporting and publishing, etc. SAS for Windows statistical software will be used throughout the course for data analysis.
STAT-776
3 Credits
As the need for causal discovery increases, and supportive data are increasingly available, there is a growing need to understand causal inference methods and applications beyond experiments. This course is a survey of a broad array of topics including the concepts of causal inference, causal inference methods, and applications of and implementation of causal inference techniques. Topics will include causal diagrams, and causal inference methods such as propensity score methods, instrumental variables, and methods for time-varying exposures Implementation of the methods using statistical software will be addressed. Prerequisites include a regression course and a statistical software course.

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