Methods I: Linear and Generalized Linear Models

Catalog description

This course offers a comprehensive foundation in statistical theory and the practical application of generalized linear models (GLM) for clinical and human health research. It will cover diverse applications of GLMs tailored to common outcomes found in health data, such as continuous, binary, count, and survival data. The curriculum spans from exploratory data analysis to model building, diagnostics, and predictive analytics, with an emphasis on applications of GLM theory for solving real-world data challenges. Case studies and examples will be drawn from various fields, including medical/pharmaceutical applications, public health, and social sciences. This course is specifically crafted for students enrolled in the online Master’s program who seek to gain both hands-on proficiency and a solid conceptual grasp of regression analysis principles.