Mark Tranmer

Mark Tranmer

Professor of Quantitative Social Sciences (School of Social & Political Sciences)

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Professor Mark Tranmer joined the School of Social & Political Sciences in July 2016 as Professor of Quantitative Social Science. From 1999 to June 2016 he was 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.

Research interests

Mark's methodological research interests are as follows:

  • Multilevel Models - including organisational (e.g. school, hospital) variations, area variations, social network variations, and longitudinal models.
  • Social Network Analysis - including single-level networks and multilevel networks that include connections at different levels of a population structure e.g. individual and organisational.
  • Bringing multilevel modelling and social network analysis together by including social network components in a multilevel model
  • The use of the Multiple Membership Multiple Classification (MMMC) model in social network, organisational, and geographical studies.
  • Relation Event Modelling - model-based approaches to investigating patterns in sequences of events over time for individuals, or patterns of network interaction over time.

His substantive research interests include:

  • Public health - including variations in smoking and substance use, happiness and well-being.
  • Health systems research - including variations in waiting times in hospitals and patient transfer systems; individual and organisational network variations in health research.
  • Social support for mental health and patient safety.
  • Social Stratification - including the modelling of variations in occupational status amongst families or between generations.
  • Animal Behaviour - including the modelling of interaction sequences amongst networks of animals.