Longitudinal Data Analysis

About

This course focuses on methods for analyzing longitudinal and repeated measures data. The defining feature of longitudinal studies is that measurements of the same individuals are taken repeatedly through time, thereby allowing the direct study of change over time. This type of study design encompasses epidemiological follow-up studies as well as clinical trials. The course covers many well-established methods for the analysis of longitudinal data when the response variable is continuous. Methods for discrete response variables (e.g., repeated binary responses and counts) are introduced, but not emphasized. An introductory course in biostatistics and a good background in linear regression analysis are prerequisites for this course.

Course leader

Garrett Fitzmaurice (Harvard School of Public Health)

Target group

Physicians, clinicians and public health professionals from public and private institutions who are looking for systematic training in the principles of epidemiology and biostatistics, or epidemiology applied to health care planning and evaluation. They will acquire familiarity with epidemiological and biostatistical principles and techniques and with the computational tools needed to solve practical problems.

Students in biostatistics and epidemiology, and researchers both from public and private institutions who wish to increase their familiarity with quantitative methods or to deepen their knowledge of a specific area of interest, so they can more effectively address problems in health research. They will gain knowledge in modern, advanced methods useful for health professionals engaged in clinical practice, research and teaching.

Course aim

This course focuses on methods for analyzing longitudinal and repeated measures data.

Fee info