This course provides a comprehensive survey of the statistical methods that have been recently developed for the designs and analysis of genetic association studies. Specific topics include genome-wide association studies, likelihood inference and EM algorithm, case-control sampling and retrospective likelihood, secondary phenotypes in case-control studies, haplotypes and untyped SNPs, population stratification, meta-analysis, multiple testing, winner's curse, copy number variants, next-generation sequencing studies, rare variants and trait-dependent sampling.

Prepares students for teaching introductory level courses in biostatistics. The topics discussed are: syllabus development, lecturing, encouraging and managing class discussion, evaluating student performance, test and examinations, cheating, the role of the teaching assistant, teacher-student relationships, teaching students with weak quantitative skills, teaching students with diverse backgrounds, teaching health sciences students, teaching medical students, use of audio-visual techniques, and use of computers. Each student is required to teach a certain subject to the other students and the instructor, followed by a discussion of presentation strengths and weaknesses

Provide practical skills and knowledge to complete a PhD dissertation in Biostatistics and to introduce students to the research of BIOS faculty. Students will become familiar with the process of PhD research in biostatistical methods.

Invited speakers, faculty, and advanced students discuss special topics and new research findings.

Research pertaining to a dissertation and preparing for the proposal.

Provides an in-depth exposure to specific topics not covered in regular courses, for example, statistical genetics and specialized experimental designs.

Involves intern-like participation at advanced levels on specific scholarly, research, or developmental projects. Students assume independent roles as statistical consultants and collaborators in a variety of research settings.

Research pertaining to a dissertation and preparing for the defense.

Provides the student with basic knowledge about the behavioral sciences as they are applied to public health. Content includes an overview of each discipline and current issues for students who are not enrolled in the BSHE MPH Program.

Pre-Requisites: PRS 500D as prerequisite or special permission required to enroll. The purpose of this course is to describe how behavioral and social science theories, research methods, and practice models can be used to understand and intervene upon public health problems. The social ecological model provides the conceptual framework for the course with an emphasis on the importance of primary prevention. Students will gain an understanding of how factors at the individual, intrapersonal, community and public policy levels interact to influence health over the life course. The course introduces theories at each of these levels and how to use these theories to inform intervention design. It includes a review of risk factors for the leadings causes of morbidity and mortality and a detailed discussion of how social and economic inequalities and other factors influence health (e.g., social class, culture, race/ethnicity, and gender). The course concludes with a discussion of translating knowledge to action and bringing evidence-based interventions to scale.