masthead

Links to other important ESRC programmes

Page Links :

Related Pages :

External Links:

esrc logo

ESRC National Centre for Research Methods (NCRM)

The mission of  the NCRM is to provide a strategic focal point for the identification, development and delivery of an integrated national research, training and capacity-building programme aimed at:

  • promoting a step change in the quality and range of methodological skills and techniques used by the UK social science community; and
  • providing support for, and dissemination of, methodological innovation and excellence within the UK.

The NCRM consists of a co-ordinating Hub at the University of Southampton, together with  a series of Nodes around the UK. The Director of the NCRM is Professor Chris Skinner. The Centre works closely with the ESRC Research Methods Programme and shares with this programme a joint Advisory Committee.

See http://www.ncrm.ac.uk/ for further information.

ESRC NCRM Node: Bayesian methods for combining multiple Individual and Aggregate data Sources in observational studies (BIAS)

This node aims to develop a set of statistical frameworks for combining data from multiple sources to improve the capacity of social science methods to handle the intricacies of observational data. Bayesian hierarchical models offer a natural tool for linking together many different sub-models and data sources and will be used as the basic building blocks for these developments.
Based at Imperial College, London. 

See http://www.bias-project.org.uk for further information.

ESRC NCRM Node: LEMMA: Learning Environment for Multilevel Methodology and Applications

This interdisciplinary node focuses on the quantitative multilevel analysis of data with complex structure that mirrors substantive research questions. Such complex structure includes household and family data, contextual, neighbourhood and area effects, spatial analytical models, longitudinal data structures, event-duration models, and mover-stayer models. The aim is to develop existing multilevel modelling techniques, apply them to substantive research questions, and to disseminate good practice through capacity building, training workshops and a virtual learning environment.
Based at the University of Bristol.

See http://lemma.ggy.bris.ac.uk for further information.

ESRC NCRM Node: Developing Statistical Modelling in the Social Sciences

The aim of this node is to develop and extend statistical methodology and models concentrating on substantive problems in the social sciences related to social and developmental change.  Specific methodological areas will include the development of pseudo-likelihood methods for mixed-effects statistical models, local likelihood methods for the analysis of event-history data, new models and methods for longitudinal ranked-comparison data, and joint modelling of repeated-measurement and time-to-event data. The methodological programme will involve the development of new algorithms and their implementation as packages in R, and we will organise joint meetings where engagement with both the statistics and the social science communities can occur.
Based at Lancaster University and the University of Warwick.

See http://www.cas.lancs.ac.uk/node/ for further information.

ESRC NCRM Node: Methods for Research Synthesis Programme

Before undertaking any new policy, practice or research or making personal decisions in our lives it can be useful to find out what others already know about the issue. Research synthesis can assist such processes by providing a method for identifying and synthesising the findings of primary research. Methods for research synthesis provide rigorous, explicit, transparent and accountable methods to determine what we know, how we know it, what more we need to know and how we might know it. Research synthesis needs to be question-led, as the questions we ask will determine the answers we find. Methods for Research Synthesis can also inform methods for synthesising primary data other than from research (Methods for Information Synthesis)
Based at the Institute of Education, University of London.

See http://eppi.ioe.ac.uk/EPPIWeb/home.aspx for further information.

ESRC NCRM Node: Qualitative Research Methods in the Social Sciences: Innovation, Integration and Impact (QUALITI)

QUALITI focuses on the innovation, integration and impact of qualitative research methods, paying particular attention to the social contexts in which research methods and methodologies are situated. The methodological aims include:

  • exploring the opportunities and challenges for integrating different qualitative research approaches, modes of data collection, data types and analytical strategies;
  • exploiting new opportunities for the recording, display and communication of qualitative data;
  • developing innovative and participatory methods of qualitative inquiry; and
  • enhancing the role, impact and understanding of qualitative inquiry in the public domain

Based at Cardiff University.

See http://www.cardiff.ac.uk/socsi/qualiti/ for further information.

ESRC NCRM Node: Multi-Dimensional Methods for Real Lives Research

The Real Life Methods node aims to pioneer research methods that can grasp the multi-dimensionality of everyday real life. The approach is qualitatively-driven, whilst spanning and transcending the qualitative/quantitative divide. The node’s team and programme of work is interdisciplinary and involves the creative blending of methods, and the development of context sensitive or cross-contextual forms of explanation.
Based at the Universities of Manchester and Leeds.

See http://www.reallifemethods.ac.uk/ further information.

ESRC Research Methods Programme

This programme aims to:

  • support substantively focused research that poses interesting or novel methodological issues;
  • foster work that directly enhances methodological knowledge or improves and advances quantitative and qualitative methods;
    encourage and support the dissemination of good practice, including the enhancement of training
  • programmes and training materials for the research community;
  • establish fellowships linked to research funded through this programme, or linked to existing centres of methodological excellence; and
  • promote cross-national initiatives involving substantively focused and methodologically innovative research.

Based at the Centre for Census and Survey Research, University of Manchester. See http://www.ccsr.ac.uk/methods/ for further information.

ESRC Researcher Development Initiative

The Researcher Development Initiative supports the training and development of researchers in the social sciences at all stages of their career. Established by ESRC’s Training and Development Board, RDI contributes to the development of a robust national training infrastructure intended to drive forward research training in a systematic way.
RDI aims to facilitate the production and deployment of a range of activities and resources, including student-led activities; training for research students and researchers throughout their career; regional training events; and the development and use of new tools and packages for training purposes.
The Researcher Development Initiative is linked closely with other ESRC training activities and resources, such as the National Centre for Research Methods, and the Research Methods Programme.
The RDI Co-ordinator is Ray Lee at Royal Holloway University of London.

See http://www.rdi.ac.uk/index.asp for further information.

ESRC Census Programme

This programme provides data and support services to allow users in UK Higher and Further Education institutions to access the 1971, 1981, 1991 and 2001 UK censuses.
The programme coordinator is Professor David Martin of the University of Southampton.

See http://www.census.ac.uk/ for further information.

ESRC National Centre for e-Social Science (NCeSS)

NCeSS is funded by the ESRC to investigate and promote the use of e-science to benefit social science research. The overall goal of NCeSS is to stimulate the uptake and use of emerging e-science technologies within the social sciences. To do this, NCeSS provides information, training, advice, support and online resources. NCeSS also researches the use of e-science technologies and advises on the future strategic direction of e-social science.
The Centre is made up of a co-ordinating hub, based at the University of Manchester with support from the UK Data Archive at the University of Essex, plus seven research nodes based at institutions throughout the UK.

See for http://www.ncess.ac.uk/ further information.