PHCM9517 - Advanced Biostatistics and statistical computing
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At the end of this course students will be able to apply advanced biostatistical methods to their public health and clinical research and gain the required statistical skills to write a journal article or a standard report. In particular, students will be able to correctly select the appropriate statistical analytical method to address specific research questions, conduct the selected statistical analysis using SAS software for statistical analysis, present and interpret the results appropriately and draw valid and insightful conclusions. The broad topics that will be covered in this course include: one-way analysis of variance, simple and multiple linear regression analysis, model building strategies in regression analysis to adjust for confounding and dealing with effect modification; advanced analysis of categorical data (analysis of KxK tables), logistic regression analysis for binary outcome data, regression analysis for count data (Poisson and Negative binomial regression), analysis of time to event data including life table, Kaplan-Meier survival plot, log rank test and Cox proportional Hazards model. The learning method will include formal lectures on the topics, hands-on problem solving tutorials, computer laboratory sessions to demonstrate the use of SAS software and guest presentation on the use of the methods in clinical and public health research.