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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.

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 - (Research Department of Epidemiology & Public Health)
  • Course Tutor - Dr Paola Zaninotto - (Research Department of Epidemiology & Public Health)
  • Administrator - Ms Kasia Bronk - (Organisational & Staff Development)

 

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BLOCK 1: 24 Mar-14 Apr 2015

Description:

This is a three-day course. Students should attend all sessions: 

  1. Introduction to STATA
  2. Linear Regression  
  3. Logistic Regression 
Points:5
Places Available:29
Sessions:11:00am - 1:00pm on Tue 24 Mar 2015
Public Cluster 113, 1-19 Torrington Place, WC1E 7HB (Map)
10:00am - 12:00pm on Tue 31 Mar 2015
Roberts 110, Roberts Building, Torrington Place, UCL, WC1E 7JE (Map)
1:00pm - 3:00pm on Tue 31 Mar 2015
Public Cluster Cruciform B115A, Cruciform Building, Gower St, UCL, WC1E 6BT (Map)
10:00am - 12:00pm on Tue 14 Apr 2015
Roberts 110, Roberts Building, Torrington Place, UCL, WC1E 7JE (Map)
1:00pm - 3:00pm on Tue 14 Apr 2015
Public Cluster B29, Foster Court, Gower St, UCL, WC1E 6BT (Map)
Preparatory Work:Students will need UCL computer ID to access course materials and take part in the computer practicals

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BLOCK 2: 21 Apr-5 May 2015

Description:

This is a three-day course. Students should attend all sessions: 

  1. Poisson regression
  2. Ordered and Multinomial Logistic regression 
  3. Survival analysis

PLEASE NOTE: to attend this block students must be familiar with linear and logistic regression

Points:6
Places Available:25
Sessions:10:00am - 12:00pm on Tue 21 Apr 2015
Roberts 110, Roberts Building, Torrington Place, UCL, WC1E 7JE (Map)
1:00pm - 3:00pm on Tue 21 Apr 2015
Public Cluster B29, Foster Court, Gower St, UCL, WC1E 6BT (Map)
10:00am - 12:00pm on Tue 28 Apr 2015
Roberts 110, Roberts Building, Torrington Place, UCL, WC1E 7JE (Map)
1:00pm - 3:00pm on Tue 28 Apr 2015
Public Cluster B29, Foster Court, Gower St, UCL, WC1E 6BT (Map)
10:00am - 12:00pm on Tue 5 May 2015
Roberts 110, Roberts Building, Torrington Place, UCL, WC1E 7JE (Map)
1:00pm - 3:00pm on Tue 5 May 2015
Public Cluster B29, Foster Court, Gower St, UCL, WC1E 6BT (Map)
Preparatory Work:Students will need UCL computer ID to access course materials and take part in the computer practicals. PLEASE NOTE: to attend this block students must be familiar with linear and logistic regression

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BLOCK 3: 12 May 2015

Description:

This is a full-day course. Students should attend both sessions:

  1.  Introduction to multilevel models 

PLEASE NOTE: to attend this block students must be familiar with regression and survival analysis

Points:2
Places Available:26
Sessions:10:00am - 12:00pm on Tue 12 May 2015
Roberts 110, Roberts Building, Torrington Place, UCL, WC1E 7JE (Map)
1:00pm - 3:00pm on Tue 12 May 2015
Public Cluster B29, Foster Court, Gower St, UCL, WC1E 6BT (Map)
Preparatory Work:Students will need UCL computer ID to access course materials and take part in the computer practicals. PLEASE NOTE: to attend this block students must be familiar with regression and survival analysis

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BLOCK 4: 19 May-26 May 2015

Description:

This is a two-day course.

  1. Principal components analysis and factor analysis
  2. Path analysis and Structural equation models 

 PLEASE NOTE: to attend this block students must be familiar with regression and survival analysis

Points:4
Places Available:29
Sessions:10:00am - 12:00pm on Tue 19 May 2015
Roberts 110, Roberts Building, Torrington Place, UCL, WC1E 7JE (Map)
1:00pm - 3:00pm on Tue 19 May 2015
Public Cluster B29, Foster Court, Gower St, UCL, WC1E 6BT (Map)
10:00am - 12:00pm on Tue 26 May 2015
Roberts 110, Roberts Building, Torrington Place, UCL, WC1E 7JE (Map)
1:00pm - 3:00pm on Tue 26 May 2015
Public Cluster B29, Foster Court, Gower St, UCL, WC1E 6BT (Map)
Preparatory Work:Students will need UCL computer ID to access course materials and take part in the computer practicals. PLEASE NOTE: to attend this block students must be familiar with regression and survival analysis

Page last updated: 22nd July 2010