Current facets (Pre-Master)
PhD defence of Pieter Schoonees on Tuesday 15 December 2015
On Tuesday 15 December 2015 Pieter Schoonees will defend his PhD thesis entitled 'Methods for Modelling Response Styles'. Supervisor is Professor Patrick Groenen and co-supervisor is Dr. Michel van de Velden (both from Erasmus School of Economics). Other members of the Doctoral Committee are Professor Dennis Fok (Erasmus School of Economics), Professor Fred van Eeuwijk (Wageningen UR) and Professor Emeritus Paul Eilers (Erasmus MC).
Time and location
The PhD defence will take place in the Senate Hall of Erasmus University Rotterdam and will start at 15.30 hrs.
About Pieter Schoonees
Pieter Schoonees obtained his Bachelor's degree in Actuarial Science from the University of Stellenbosch, South Africa, in 2007. He also completed postgraduate Honours Bachelor degrees in Actuarial Science (2008) and Mathematical Statistics (2009, cum laude), before completing his Master's degree in Mathematical Statistics (cum laude) in early 2011, also in Stellenbosch.
Pieter joined the Erasmus Research Institute of Management in 2011 as a PhD candidate, working on statistical models. In April 2015, he joined the Department of Marketing Management at the Rotterdam School of Management, Erasmus University as a tenure-track post-doctoral researcher. His research interests include computationally intensive statistical models, both parametric and non-parametric, statistical software development, and statistical (or machine) learning. Recently, he is interested in applying such methodology to marketing and neuroscientific problems.
His work has been published in Psychometrika, will appear in the Journal of Statistical Software, and is under review at other top journals. He has presented at international forums such as the International Conference on Computational Statistics, the International Federation of Classification Societies Conference, the ISMS Marketing Science Conference and the Annual Meeting of the Psychometric Society. Pieter was a visiting researcher at the Department of Psychology of the University of Zurich in the fall of 2014.
Abstract of 'Methods for Modelling Response Styles'
Ratings scales are ubiquitous in empirical research, especially in the social sciences, where they are used for measuring abstract concepts such as opinion or attitude. Survey questions typically employ rating scales, for example when persons are asked to self-report their perceptions of films or their job satisfaction. Yet, using a rating scale is subjective. Some persons may use only the middle of the rating scale, whilst others choose to use only the extremes. Consequently, persons with the same opinion may very well answer the same survey question using different ratings. This leads to the response style problem: How can we take into account that different ratings can potentially have different meanings to different persons when analysing such data?
This dissertation makes methodological and empirical contributions towards modelling rating scale data while accounting for such differences in response styles. The general approach is to identify individuals in the data which exhibit similar response styles, and to extract substantive information only within such groups. These elements naturally lead to the synthesis of cluster analysis and dimensionality reduction methods. In order to identify these response styles, responses to multiple survey questions are used to assess within-subject rating scale usage. Both non-parametric and parametric approaches are formulated and studied, and accompanying open-source software implementations are made available. The added value of using the developed algorithms is illustrated by applying these to empirical data. Applications range from sensometrics and brand studies, to psychology and political science.