流行病學研究設計

Following the introductory epidemiology course, this advanced course is designed to expand students’ scientific understandings of modern epidemiology, and emphasizes the practices of epidemiologic data analysis and interpretation. This course covers: advanced concepts in epidemiologic causal inference, advanced study designs, epidemiologic data analysis and interpretations of different study designs. Objectives After successful completion, students are expected to - Apply DAG to visualize and analyze complex epidemiologic topics - Use appropriate study design to address epidemiology research questions - Critically and appropriately choose study design and analytical strategies - Understand the sciences and arts of model building in epidemiology - Develop an analytical plan for secondary data analysis project (proposal), and conduct it - Correctly present and interpret epidemiologic results

There is no required textbook, but there will be required readings for particular lectures. Nevertheless, below we list books that would be helpful. The NYMU library has electronic access to these books. - Timothy L Lash et al. (2021) Modern Epidemiology, Ed. 4. Wolters Kluwer. - Hulley, S. B. (Ed.). (2007). Designing Clinical Research. Lippincott Williams & Wilkins. - Eric Vittinghoff, David V. Glidden, Stephen C. Shiboski, Charles E. McCulloch (2012) Regression Methods in Biostatistics: Linear, Logistic, Survival, and Repeated Measures Models. Springer. - For uses of statistical packages to conduct basic data analysis: https://stats.idre.ucla.edu/#