The major components of research activities are covered, including concepts of health, formulation of research questions, literature reviews, study designs, selection of study populations, choice of measuring instruments, and study interpretation issues such as determination of causality and the effectiveness of clinical and community interventions. This course introduces students to the main elements of clinical trial design, execution, and analysis. Students' grasp of clinical trial methodology will allow students to prepare successful grant applications. This course will examine biostatistical methods for the analysis of categorical data. The course begins with an examination of methods for analyzing simpler contingency tables, including measures of association.
Primary attention is given to log-linear models and logistic regression.
The focus can be adjusted to suit the needs of students. This course will consider important statistical issues relating to design, analysis and interpretation of randomized clinical trials. Specific topics will include issues in sample size determination, sequential methods, repeated data evaluation, data monitoring, analysis of survivorship data and competing risks, crossover trials, large simple trials, factorial designs, economic evaluation in clinical trials, cluster randomization and meta analysis. This course will be taught in small group tutorials. The emphasis of this course is on the concepts and techniques associated with planning and implementing the data management aspects of health research projects.