e-STAT: National Centre for E-social Science Quantitative Node

Project Details


The e-Stat project, September 2009 until December 2012 is an exciting new node in the Digital Social Research programme. It brings together academics working in statistics and computer science.

The statisticians are primarily researching statistical methodology and statistical software development for complex statistical models that are used in the social sciences and other disciplines. The main statistical group involved in this project are based at the Centre for Multilevel Modelling at the University of Bristol where they have been supported for many years by the ESRC most recently through their LEMMA 2 node in the NCRM programme. They are joined by collaborators at the Universities of Manchester and Stirling and the Institute of Education, London who themselves have involvement on ESRC funded research projects.

The computer science input comes from a team at the University of Southampton who are world renowned experts in the research areas of e-Science and Multimedia. They have been funded by several research councils to develop research on projects including myExperiment and LifeGuide. They are backed up by software engineers at the Centre for Multilevel Modelling and a consultant, Bruce Cameron.

Through the synthesis of this statistical and computing expertise the project aims to realise the ESRC's vision of e-science enabling cutting edge methodological developments to help quantitative researchers do new and better research and to provide learning pathways to bring these cutting edge developments into working practices of quantitative social sciences.

Through this web site we hope to give a flavour of the project’s aims and objectives and over time fill the site with project outputs and prototype software. The project was initiated by our much-missed colleague Professor Jon Rasbash and we have named the software package STAT-JR in his honour.
Effective start/end date1/10/0930/10/12

Structured keywords

  • SoE Centre for Multilevel Modelling


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