课程时间表
2020/21 年流行病学与生物统计学短期课程现已接受报名
第一学期：2020年9月-12月
第二学期：2021年1月-3月
第三学期：2021年4月-6月
Term I
BIOS5001 Introduction to Biostatistics
This course introduces basic statistical concepts and methods. The emphasis of the course is on practical applications: choosing the correct method for particular datasets and correct interpretation of the analysis results. Examples from different disciplines of public health including chronic and infectious disease epidemiology, environmental health, and health policy will be used to illustrate the use of biostatistical methods in answering important public health questions.
BIOS5005 Clinical Trials
The objective of this course is to provide students with a theoretical and practical knowledge of the issues involved in the design, conduct, analysis and interpretation of randomized clinical trials. We will discuss the basic principle of randomization and its importance, proper randomization and blinding procedures, choice of control arm, the importance of clear definition of endpoints, methods to calculate sample size, other statistical considerations and ethical issues in clinical trials. Attention will be given to the problems of conducting clinical trials in both single center and multi-center, and covers trials initiated by industry as well as trials in academic setting. Students will be trained to develop skills to properly design clinical trial, critically analyze and carry out research and to communicate effectively.
EPID5001 Introduction to Epidemiology
This course will introduce basic epidemiology to students including introduction to epidemiology, applied health research methods, designing and conducting epidemiological studies (descriptive, case-control, cohort, systematic reviews).
Term II
BIOS5002 Linear Models
This course will provide a foundation for the practical analysis of data for which the primary outcome is a continuous variable. The course will begin with an introduction to ‘real-world’ data analysis with a motivating example looking at predictors of infant birthweight in Hong Kong. Methods for multivariate analysis of predictors of continuous outcomes including one-way and two-way ANOVA and multiple linear regression will then be discussed in detail with an emphasis on correct use of these methods in practice.
BIOS5003 Categorical and Survival Data Analysis
This course will provide a foundation for the practical analyses of categorical and time to event (survival) data. The course will cover the use of logistic regression models for use with binary outcomes and Cox proportional hazards regression models for time to event outcomes. Practical application of these models will be emphasized and model building and the checking of model assumptions will be covered in detail.
BIOS5007 Pharmaceutical Statistics Computing in SAS
The objective of this course is to familiarize students with the SAS software for pharmaceutical application. The course starts with the introduction of basic SAS skills followed by using SAS to draw tables, figures, and listings (TFL) and to analyze medical data. Practical scenarios will be given to students to understand the needs of SAS in pharmaceutical industry.
EPID5002 Epidemiological Study Designs
This is a follow up of course Introduction to Epidemiology (EPID5001) to provide further concepts and application of epidemiology. Topics will include further concepts in epidemiological study designs and application of concepts to the planning and design of epidemiological studies.
EPID6002 Selected Topics in Epidemiology
The course involves a series of guest lecture seminars in which methodological aspects of various areas of epidemiological research are discussed and elaborated.
Term III
BIOS6001 Topics in Linear Models
This course will cover advanced statistical modelling techniques for use with complex datasets. Topics will include Poisson and Negative Binomial regression for count outcomes, repeated measures ANOVA, GEE models and multilevel models for longitudinal data and multilevel models for clustered data.
BIOS6005 Pharmaceutical Bioinformatics
The course will provide a broad overview and introduction to bioinformatics and its applications in pharmaceutical industry. Topics will cover (1) basic bioinformatics methods: hierarchical clustering, lasso, random forest, LDA, PCA, boosting, bootstrapping, etc. (2) data sequencing and management: microarray data, GWAS data, the raw data treatment and analysis method, batch effect and normalization, parallel programming in R; (3) phylogenic analysis; (4) Chemobioinformatics modeling, 3D structure, chemical - protein relation leading to drug discovery.
BIOS6006 Artificial Intelligence Methods for Medical Research and Pharmaceutical Science
This course is an advanced module for students who are interested to understand how various artificial intelligence approaches including machine-learning and deep-learning can be used on top of traditional biostatistics methods. It emphasizes on practical knowledge and skills needed for doing this kind of research leveraging on our experience and proprietary development of the Automatic Retinal Image Analysis (ARIA) and the Bioinformatics and Genomic research with significant machine-learning and deep-learning components. On top of sharing of the real life experience other important research areas in medical and pharmaceutical science would also be discussed.
EPID5003 Analysis of Epidemiological Data
This module prepares students on collection, management, analysis and interpretation of epidemiological data with consideration for analysis of special data such as age-period-cohort effect.
EPID6001 Appraisal of the Methods of Epidemiological Studies
The course will include a series of tutorials for appraising the methods of commonly used epidemiological study designs. In each tutorial, a published study of a specific design (e.g., randomized controlled trial) will be selected and presented and questions regarding the methods of the study will be asked. Students need to carefully read and discuss the questions beforehand and further discuss with the tutor and peers in the class.
EPID6003 Nutritional Epidemiology
In this course, you will learn about the methods used to assess dietary intakes and how to overcome limitations in assessing such a complex ‘exposure’. Nutrient intakes and dietary patterns in different population groups will be illustrated and key diet-disease associations will be presented. Finally, some of the challenges in interpreting nutritional epidemiology evidence and practical issues in communicating findings will be covered.