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Statistical Analysis Methods for Epidemiology and Social Sciences

Course Description

This advanced level course will provide training in some of the common statistical modelling methods used in epidemiological and social sciences research. It consists of lectures followed by practical sessions based on the STATA statistical package. Students will work with example data sets taken from epidemiological surveys. During the practical sessions students work through exercises individually, with the help of tutors.

The course will cover:

  • Linear regression (for analysis of continuous outcomes such as blood pressure).
  • Logistic regression (for analysis of binary outcomes such as presence or absence of an illness).
  • Poisson, ordered and multinominal logistic regression (for count, ordinal and nominal outcomes).
  • Survival models (applicable to prospective studies of mortality and disease incidence).

The course will also provide an introduction to some more advanced techniques used in health and social sciences research together with examples of their applications:

  • Multilevel models allow the study of influences on health that operate at different levels, such as the study of associations between area characteristics and health of individuals.
  • Principal components and factor analysis are data reduction techniques used to form new variables which are linear composites of the original variable in the former models and latent unobserved construct in the latter models.
  • Path models and structural equation models allow the testing of complex models involving hypothesised pathways between risk factors and disease.

Full Course Timetable 

The course is suitable for students who have a knowledge of basic statistical methods and linear regression analysis. Students should have some prior experience of using a statistical package such as SPSS to gain the most out of the course. An introduction to using STATA will be provided as part of the course. Students who attend the course will also have an opportunity to book a one hour individual consultation with a statistician. Details of how to book this will be provided at the beginning of the course.

Students from outside the Division of Population Health should contact the course tutor, Jenny Head to discuss whether the course is appropriate for them before registering.

Students will need a UCL computer ID to access course materials and take part in the computer practicals.

"These courses are more than worthwhile - the material is really good - I think many students and researchers would buy this as a new hands-on introduction to statitics and Stata if it were stringed together as a book"

Introduction to STATA - "This course is beneficial not only for those who have recently started working on STATA but also for people who are self-taught. It provides hints and tips on everyday commands and syntax that are often overlooked and which can make life much easier."

Linear Regression - "As someone with probably less experience than most of the others on the course, I was worried that I'd be out of my depth. But the topic was very clearly explained, and the computer practical helped to consolidate that."

Survival Analysis - "This course was interesting and will be useful if you intend to do longitundinal analysis."

Introduction to Multilevel Models - "The combination of lectures and computer sessions works well. Course material is excellent and the STATA tools are well integrated."

Researcher Development Framework Categories

A1) Knowledge base
A2) Cognitive abilities

Course Recommended for

This course is particularly relevant to the following groups:

  • Students in Social & Historical Sciences
  • Students in Life Sciences
  • Students in Medical Sciences
  • Students in Population Health Sciences

Course Organisers

  • Course Tutor - Prof Jenny Head - (Research Department of Epidemiology & Public Health)
  • Course Tutor - Dr Mai Stafford - (MRC Unit for Life Long Health and Ageing)
  • Course Tutor - Dr Paola Zaninotto - (Research Department of Epidemiology & Public Health)
  • Administrator - Ms Kasia Bronk - (Organisational & Staff Development)


BLOCK 1: 24 Mar-14 Apr 2015 expand

BLOCK 2: 21 Apr-5 May 2015 expand

BLOCK 3: 12 May 2015 expand

BLOCK 4: 19 May-26 May 2015 expand

Page last updated: 23rd April 2015