Mark Tranmer joins the School of Social & Political Sciences in July 2016 as Professor of Quantitative Social Sciences. Since 1999, he has been based in Social Statistics in the School of Social Sciences at the University of Manchester, leading the Statistical Modelling Group, as well as being a member of the executive committee of the Mitchell Centre for Social Network Analysis, and a member of the Cathie Marsh Institute for Social Research (CMIST). He was awarded a PhD in Social Statistics from the University of Southampton in 1999, having previously studied statistics at BSc and MSc level in Sheffield.
His methodological research focus began in multilevel modelling, including the development of an approach to combine individual and aggregate data to assess individual and area variations in social, political and health variables. Recently, he has been interested in developing multilevel approaches for assessing the way in which the attributes of a network node (e.g. educational, health, and well-being measures for a person) co-vary with the attributes of other nodes to which they are connected (e.g. through friendship). He has further extended these approaches to assess changes over time in these variations. These methodological developments highlight his general interest in understanding social population structure from a geographical, organisational, network, and temporal perspective.
Substantive applications of these methods include assessing individual and area variations in the take-up of post-compulsory education, inequalities in health and well-being, variations in crime by local area, variations in civic and political engagement in the UK and Europe, changes in occupational tie structures in the UK over time, network variations in hospital waiting times and patient safety, and area, school, and network variations in drinking, smoking and drug use in six European countries.
Another of his recent research interests is the application of the Relational Event Model (REM) to assess persistence and reciprocity of social interactions over time, as well as the use of the REM for model-based approaches to the analysis of sequences, such as the life course, and its association with the health and well-being of people in later life.
He has published in a range of substantive and methodological journals. He was recently guest co-editor of a special edition of “Social Networks” on Multilevel Social Networks. He has honorary senior and professorial positions at the Universities of Stirling, Wollongong (Australia) and USI (Switzerland). He has also taught a range of statistical methods courses at various levels in the UK and internationally to academic and non-academic audiences, and supervised PhD students to completion for a range of topics in the social and political sciences.
His methodological research focus began in multilevel modelling, including the development of an approach to combine individual and aggregate data to assess individual and area variations in social, political and health variables. Recently, he has been interested in developing multilevel approaches for assessing the way in which the attributes of a network node (e.g. educational, health, and well-being measures for a person) co-vary with the attributes of other nodes to which they are connected (e.g. through friendship). He has further extended these approaches to assess changes over time in these variations. These methodological developments highlight his general interest in understanding social population structure from a geographical, organisational, network, and temporal perspective.
Substantive applications of these methods include assessing individual and area variations in the take-up of post-compulsory education, inequalities in health and well-being, variations in crime by local area, variations in civic and political engagement in the UK and Europe, changes in occupational tie structures in the UK over time, network variations in hospital waiting times and patient safety, and area, school, and network variations in drinking, smoking and drug use in six European countries.
Another of his recent research interests is the application of the Relational Event Model (REM) to assess persistence and reciprocity of social interactions over time, as well as the use of the REM for model-based approaches to the analysis of sequences, such as the life course, and its association with the health and well-being of people in later life.
He has published in a range of substantive and methodological journals. He was recently guest co-editor of a special edition of “Social Networks” on Multilevel Social Networks. He has honorary senior and professorial positions at the Universities of Stirling, Wollongong (Australia) and USI (Switzerland). He has also taught a range of statistical methods courses at various levels in the UK and internationally to academic and non-academic audiences, and supervised PhD students to completion for a range of topics in the social and political sciences.
