Summary of course:
In recent years the use of paradata (‘field process data') has received increasing attention in survey research. Typical examples of paradata are key-stroke files, which capture navigation through the questionnaire, and time stamps, which provide information such as date and time of each call attempt or the length of a question-answer sequence. Other examples are interviewer observations about a sampled household or neighbourhood, recordings of vocal properties of the interviewer and respondent, and information about interviewer calls and interviewing strategies. It is hoped to use paradata for the improvement of survey designs, survey quality and analysis. It also offers opportunities for efficiency gains and cost savings in surveys. This course introduces participants to the practices and cutting-edge research in the up-and-coming field of paradata. It is aimed at both producers and users of paradata, both at senior and junior levels.
This course is part of a 3.5 year ESRC research project conducted by 4 of the presenters (Gabriele Durrant, Frauke Kreuter, Peter Smith and Olga Maslovskaya) (grant number: RES-062-23-2997). The event is also organised jointly with the Social Statistics Section of the Royal Statistical Society.
The course will have good practical emphasis through examination of case-studies and research examples.
Course Content:
This course covers the great potential of paradata for social survey research. The course will give an introduction and overview of methodological issues involved in the collection and analysis of paradata. We will discuss several research examples including, but not limited to, investigating the use of paradata:
Case studies will draw attention to the challenges in automated data capturing and modelling of the complex structure of paradata. The course will also discuss analysis of paradata, in particular the use of call record data.
Course Objectives:
The objective is to provide participants with an overview of best practices and cutting edge research on the use of paradata, and to help participants gain a thorough understanding of the role of paradata in increasing survey quality and reducing total survey error.
The course will have good practical emphasis through examination of case-studies and research examples.
Target Audience:
The course is aimed at both producers and users of survey data, at both senior and junior levels. The course is aimed equally at researchers from academia, government and the voluntary and private sector, including market research and statistical agencies. The course is designed for researchers new to this topic as well as for those who already have experience in this area.
Course Fee:
Thanks to continued ESRC funding we are able to offer this course at reduced rates as follows:
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.
Course places are limited and early registration is strongly recommended.
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.
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.
Duration:
This is a 2 day course. The course will begin with coffee and registration from 9.00am and formal teaching will begin at 9.30am and end at 5.30pm on the first day. On the second day, teaching will begin at 9.30am and finish at 4.00pm. (times to be confirmed)
Pre-requisites:
A working knowledge of survey research methods will be assumed. Participants are expected to have a basic knowledge of survey statistics (comparable to the level of the CASS Survey Data Analysis I and II courses).
Course Materials:
Participants will receive written course notes.
The Instructors:
Frauke Kreuter
is Associate Professor in the Joint Program in Survey Methodology at the University of Maryland; Professor of Statistics at Ludwig Maximilian University of Munich, Germany; and head of the Statistical Methods Research Department at the Institute for Employment Research (IAB) in Nuremberg, Germany. She is the editor of a recent book on this topic by Wiley (Improving Surveys with Paradata: Analytic Uses of Process Information). She has published extensively on the use of paradata for nonresponse adjustment, measurement error and the use of paradata in managing and improving survey data collection. She is co-investigator on the ESRC-funded research project 'Use of Paradata in Cross-SEctional and Longtidunal Surveys'. She works closely with a wide range of survey agencies both in the US and Europe.
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.
with contributions from:
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.
Peter W. Smith
is Professor of Social Statistics at the University of Southampton and Director of the Southampton Statistical Sciences Research Institute. He is co-investigator on the ESRC-funded research project ‘Use of Paradata in Cross-Sectional and Longitudinal Surveys'. He has published extensively in the area of graphical modelling, exact inference, nonresponse and longitudinal data. He has taught a wide range of statistical courses at undergraduate and postgraduate level, including short courses for CASS.
Mario Callegaro
is a Survey Research Scientist at the Quantitative Marketing Team at Google UK. He has contributed to the above mentioned book on paradata and has extensive experience in Web surveys.
Preparatory Reading:
For those who would like to do preparatory reading the following references may be useful as background material. Please note that this reading is optional and it will not be assumed that participants have done any preparatory reading.
Special Issue on Paradata published by the Journal of the Royal Statistical Society, Series A, 2013 (176, 1), edited by Gabriele Durrant and Frauke Kreuter (Guest Editors): The Use of Paradata (Process Data) in Social Survey Research. •Kreuter, F. (ed.) (2013) Improving Surveys with Paradata: Analytic Uses of Process Information, Wiley.
Durrant, G.B., D’Arrigo, J. and Steele, F. (2013): Analysing Interviewer Call Record Data by Using a Multilevel Discrete-Time Event History Modelling Approach, Journal of the Royal Statistical Society, Series A, Special issue: The Use of Paradata in Social Survey Research 176, 1, 251-269.
Book on this topic:
Frauke Kreuter has just published an edited book (with contributions from Gabriele Durrant, Mario Callegaro and others) titled ‘Improving Surveys with Paradata: Analytic Uses of Process Information, by Wiley (2013).
More information on the book can be found
here
.
The book provides an excellent resource on recent developments on paradata and will support the contents of this course.