Summary of Course:
This course provides a good introduction to applied regression methods for survey data. The course focuses on logistic regression and multinomial logistic regression. Models for ordinal data will also be introduced. At the beginning of the course, basic principles of multiple linear regression will be reviewed.
Course Objectives:
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To introduce participants to multivariate statistical methods for analysing survey data (review of multiple linear regression, introduction to logistic and multinomial regression, introduction to models for ordinal data).
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To provide hands-on experience of analysing data.
Course Content:
This course will include the following topics:
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Review of linear regression
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Logistic regression
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Diagnostics and Model Selection
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Multinomial logistic regression
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Introduction to methods for ordinal data
The course will include computer workshops using SPSS so that participants can work through examples and practical exercises.
Target Audience:
The course is aimed at researchers who need to analyse or interpret 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.
Course Fee:
Thanks to continued ESRC funding we are able to offer this course at reduced rates as follows:
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£30 per day for UK registered students
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£60 per day for staff at UK academic institutions, RCUK funded researchers, public sector staff and staff at registered charity organisations
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£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.
Deadline and Refunds:
Course places are limited and early registration is strongly recommended. Please be aware that we will only hold a place without payment for a limited time.
Please refer to the terms and conditions of the University of Southampton online store when booking. An administration charge of £30 may apply for cancellations. No refunds can be provided for cancellations less than 28 days prior to the start of the course.
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. Maps and travel information are available from the University of Southampton
Travel Page
. This also includes a map of the Highfield Campus. Building 39 is at the end of Salisbury Road edging onto Southampton Common.
Duration:
Times are to be confirmed: 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.)
Pre-requisites:
Participants of this course should have some prior statistical knowledge covering inference and linear regression modelling. This course is designed to follow on from the CASS Survey Data Analysis II course. Participants not registered on the CASS Survey Data Analysis II course are of course still very welcome to attend this course.Course Materials:
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.
The Instructors:
Dr Nikos Tzavidis
is a Senior Lecturer in Social Statistics at the Division of Social Statistics and at the Southampton Statistical Sciences Research Institute at the University of Southampton. He has worked extensively on issues related to the use of quantile models in small area estimation and poverty mapping. He is specialised in quantile regression, small area estimation, robust models, spatial analysis and applications of multilevel and multivariate multilevel models in psychology and psychiatry. He is currently involved in developing quantile random effects models, M-quantile models for binary and count data, quantile contextual value added models, robust models for small area estimation and poverty mapping, models for estimating income distribution functions at disaggregated geographical levels and spatial models for poverty mapping and Mean Squared Error estimation in small area estimation. He has taught courses in small area estimation, quantile regression, generalised linear models, multilevel models, and longitudinal data analysis at postgraduate level at the Universities of Manchester, Southampton and at the Institute of Education, University of London and in external programmes of short courses. Dr Tzavidis has participated in research programmes at National, European and International level. He recently completed work on an EU FP7 project on small area models for estimating income and poverty. He recently also completed a project on applications of multivariate multilevel models to psychiatry data, which was funded by the British Academy. He is also currently advising a government research department (COLMEX) in Mexico on the implementation of small area models for poverty estimation.
Dr Gabriele B Durrant
is Reader at the Southampton Statistical Sciences Research Institute (S3RI) at the University of Southampton. Her research interests include modeling of paradata, analysis of interviewer effects, nonresponse in sample surveys and multilevel modeling. She is currently the Principal Investigator of a 3.5 year ESRC funded research project on the ‘The Use of Paradata in Cross-Sectional and Longitudinal Surveys'. She previously was the PI of a 3.5 year ESRC funded research project on ‘Analysis of Nonresponse in Hierarchical Surveys'. She has published widely in the area of paradata and nonresponse. Gabriele teaches a wide range of statistical courses for professional development.
Dr Olga Maslovskaya
is a Postdoctoral Research Fellow working on the ESRC-funded ‘The Use of Paradata in Cross-Sectional and Longitudinal Surveys' at the Southampton Statistical Sciences Research Institute (S3RI) at the University of Southampton. Olga holds an MA in European Policy and Politics from the Department of Government, University of Manchester and an MSc in Social Statistics - Research Methods from the Division of Social Statistics, University of Southampton. She also holds a PhD from the Division of Social Statistics, University of Southampton. Olga has been involved in the teaching of a wide range of statistical courses at both undergraduate and postgraduate level, as well as short courses for professional development in the UK and abroad.
Preparatory Reading:
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.
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Agresti, A and Finlay, B. (2008) Statistical Methods for the Social Sciences, 4th edition, Pearson Prentice Hall.
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Kleinbaum, D.G. and Klein, M. (2010) Logistic regression: a self learning text, Springer, 3rd Edition.
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Kleinbaum, D., Kupper, L.L., Nizam, A. and Muller, K.E. (2007) Applied regression analysis and other multivariate methods. Duxbury Press, Pacific Grove. 4th Edition.
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