Venue: Highfield Campus, University of Southampton, UK
Presenter: Dr Denise Silva
Dates of Course: Tuesday 1st - Thursday 3rd May 2012
This course has already run. Please check the course listings for a future course.
Summary of Course:
This course focuses on regression methods for survey data. Topics include a review of multiple linear regression. The course then focuses on logistic regression and multinomial logistic regression. If time allows, models for ordinal data will be introduced.
- To introduce participants to multivariate statistical methods for analysing survey data (review of multiple linear regression, introduction to logistic and multinomial regression).
- To provide hands-on experience of analysing data.
This course will include the following topics:
- Linear regression
- Handling categorical variables and interactions
- Logistic regression
- Multinomial logistic regression
The course will include computer workshops so that participants can work through examples and practical exercises.
The course is aimed at researchers who need to analyse survey data, especially those in the social, economic, educational and medical sciences. Participants should already be familiar with basic statistical theory including inference and linear regression. Participants may be researchers working in academia, local or central government, survey agencies, market research, the voluntary or the private sector.
Participants of this course should have prior statistical knowledge covering inference and linear regression modelling. This course is designed to follow on from the CASS Survey Data Analysis II course, however, participants not attending the CASS Survey Data Analysis II course are very welcome if they have the appropriate prior knowledge.
Participants will receive written course notes.
Please bring a calculator for the workshops and a USB memory stick to save your outputs from the computer workshops.
For participants who wish to do background reading, the following references may be useful. Please note that although reading is optional, participants who have little statistical background are strongly advised to look at one of these references.
- Agresti, A and Finlay, B. (2009) Statistical Methods for the Social Sciences, 4th edition, Pearson Prentice Hall.
- Kleinbaum, D.G. and Klein, M. (2010) Logistic regression: a self learning text, Springer, 3rd Edition.
Kleinbaum, D., Kupper, L.L. and Muller, K.E. (2008) Applied regression analysis and other multivariate methods. Duxbury Press, Pacific Grove. 4th Edition.
Dr Denise Silva is a Principal Methodologist at the Brazilian Institute of Geography and Statistics and a Senior Lecturer at the National School of Statistical Sciences in Rio de Janeiro, Brazil. She previously worked as a Senior Lecturer at the Southampton Statistical Sciences Research Institute (S3RI) at the University of Southampton and as a Principal Methodologist at the UK Office for National Statistics (ONS). She has taught a wide range of statistical courses as part of CASS, the MSc in Social Statistics, the BSc in Statistics and the MSc in Population Studies and Social Surveys. She also has several years of experience working in the design and analysis of sample surveys. Her main research interests focus on small area estimation, time series analysis, survey sampling and statistical modelling in the social sciences. She completed her PhD in Statistics at the University of Southampton and has an MSc and a BSc in Statistics.
£30 per day for UK-registered students. £60 per day for staff from UK academic institutions (including research centres), ESRC funded researchers and UK registered charitable organisations. £220 per day for all other participants. The course fee includes course materials, lunches and morning and afternoon refreshments. Travel and accommodation are to be arranged and paid for by the participant.
Location and Accommodation:
The course will be held at the Southampton Statistical Sciences Research Institute, Building 39, University of Southampton, Southampton, SO17 1BJ. Participants will need to make their own accommodation arrangements. Further information on accommodation and course location is available here.
The course will begin with coffee and registration at 9.30 with formal teaching starting at 10.00am on the first day. The course finishes at about 2.30pm on the last day. Afterwards there will be an opportunity for participants to ask questions about the course and to discuss with the instructor how to analyse their own data (until about 4pm). (Course participants are welcome to bring their own data.)