Residency credit for dissertation research after the qualifying examination. Students may register for this course in the semester of the qualifying examination. A minimum of two semesters are required as well as continuous enrollment (Fall and Spring) until the dissertation is completed and defended.
Individually directed research and reading in particular aspects of medical behavioral science under the supervision of one or more members of the faculty. May be repeated up to a maximum of 12 hours.
With the advice and approval of his or her faculty adviser, the first- year student may choose approved electives offered by the Department of Behavioral Science. The intent is to provide the student an opportunity for exploration and study in an area which supplements and/or complements required course work in the first-year curriculum. Pass-fail only.
This course aims to improve the student's ability to communicate with patients and the public in an empathetic and professional manner. Methods of obtaining necessary health information from all types of patients are taught.
With the advice and approval of his or her faculty adviser, the second-year student may choose approved electives offered by the Department of Behavioral Science. The intent is to provide the student an opportunity for exploration and study in an area which supplements and/or complements required course work in the second-year curriculum. PASS-FAIL ONLY.
BST 230 provides students with an introduction to statistical concepts that are important for solving real-world public health problems. This course will present statistical principles and associated scientific reasoning underlying public health practice and health policy decision- making. Topics include data visualization, summary statistics, statistical inference, study design and data analysis, and strategies for articulating and evaluating claims using statistical constructs.
BST 230 provides students with an introduction to statistical concepts that are important for solving real-world public health problems. This course will present statistical principles and associated scientific reasoning underlying public health practice and health policy decision- making. Topics include data visualization, summary statistics, statistical inference, study design and data analysis, and strategies for articulating and evaluating claims using statistical constructs.
BST 635 covers basic concepts on databases with applications to public health. Students will learn how to program in SAS, the leading statistical analysis system. SAS skills include managing data, using SQL, generating descriptive statistics, visualizing data, writing reports, writing MACROs, and programming using SAS.
BST 663 is an applied first course in the analysis of categorical data. Topics for categorical data include methods for proportions, rates, ratios, relative risks, risk ratios, and odds ratios. Cochran-Mantel- Haenzel tests, exact tests, logistic regression, time to events and life table methods, and generalized least square methods will be discussed with applications in public health, clinical and translational trials.
This course, the second in a two-semester sequence in regression modeling, covers regression models for outcomes which are not normally distributed, such as binary and count data. The course will cover the generalized linear model framework, multivariate maximum likelihood theory, logistic regression, Poisson regression, and nominal and ordinal logistic regression models, as well as approaches for building models and checking assumptions. The course will include the use of computing tools to apply these models to real data.
