National Centre for Research Methods Phase 1 (2005-8)

Hub: University of Southampton

The founding director of NCRM was Prof Chris Skinner and the centre comprised a coordinating hub at the University of Southampton and a first phase of research nodes.  NCRM’s original Typology of Research Methods in the Social Sciences was developed during this period, and the training events programme established. The centre initially took forward a range of activities from ESRC’s former Research Methods Programme, including organization of the Research Methods Festival 2008 at the University of Oxford, and commenced the first of our centre-linked PhD students and collaborative projects. In 2007 the centre developed the ReStore project, a repository of online research methods websites from related ESRC investments.  During this period the NCRM nodes were:


BIAS: Bayesian methods for combining multiple Individual and Aggregate data Sources in observational studies

Principal Investigator: Professor Nicky Best

Host Institution: Imperial College, London

Legacy Website: BIAS Project

Node Publications: Node Publications

BIAS (Bayesian methods for combining multiple Individual and Aggregate data Sources in observational studies) was interested in modelling the complexities and core processes that underlie observational social science data and in developing a set of statistical frameworks for combining data from different sources.

These data include aggregate level data, longitudinal studies, multilevel data and surveys amongst others. As these data are notoriously full of missing values, non-responses, selection biases and other idiosyncrasies, simple analyses can be very misleading. Further, it is typically the case that a single dataset fails to provide all the necessary information, thus to answer relevant research questions it is necessary to combine datasets from multiple sources.

The researchers at BIAS aimed to construct a comprehensive set of inter-dependent sub-models to cater for the complex structure in the data. To do this, they used Bayesian hierarchical and graphical models as they offer a natural tool for linking together many different sub-models and data sources. The BIAS project also ran courses in Bayesian hierarchical models and small area estimation as well as disseminating its research and providing computer code to run the models.


Lancaster-Warwick node

Principal Investigator: Professor Brian Francis

Host Institutions: Lancaster University, University of Warwick, University of Stirling

Legacy Website: Lancaster-Warwick Node

Node Publications: Node Publications

Lancaster-Warwick node's focus was to promote good statistical modelling in the social sciences through training and also to develop new statistical modelling methodology for longitudinal and other correlated data. Researchers at Lancaster-Warwick applied these new developments to important social science problems in criminology, developmental psychology and sociology.

Lancaster-Warwick research programme focused generally on development and changes over time. Thus the criminology research strand was concerned with patterns of activity and transitions from one activity type to another; the sociology strand is focused on changing attitudes, and the developmental psychology strand is concerned with the development of cognitive ability in young children.

Researchers at Lancaster-Warwick developed methods for the analysis of longitudinal criminal careers and the detection of local patterning; for the longitudinal analysis of ranked and partially ranked data. They also investigated new methods for fitting complex random effects models (such as composite likelihood) and exploring the use of graphical models in a psychology setting.

Lancaster-Warwick's comprehensive training programme covered a wide range of statistical and other methods, and this was supplemented by a range of workshops and master classes on more specialist topics.



Principal Investigator: Professor Harvey Goldstein

Host Institution: University of Bristol

Legacy Website: Centre for Multilevel Modelling

Node Publications: Node Publications

LEMMA was an interdisciplinary node specialising in the 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.

LEMMA work in Phase 1 included:

  1. Important and much-needed methodological developments in the specification and estimation of multilevel models including the analysis of non-hierarchical structures, complex dependencies between structures and latent-class models; all these developments will be implemented in appropriate software. An unrestricted version of the MLwiN is software freely available to the ESRC ‘constituency’ for the lifetime of the project;
  2. A variety of integrated flagship projects using this methodology to research important social science questions; these will not only serve to demonstrate the methodological developments but will also be substantively important in their own right.
  3. Extensive capacity building and research training in the analysis of data with complex structure; in addition to a series of face to face workshops we will establish a multilevel modelling virtual learning environment(VLE) which is designed to initiate, develop, and support geographically-dispersed researchers.

Please note that LEMMA was also funded in Phase 2 (LEMMA II) and Phase 3 (LEMMA3).


Methods for Research Synthesis (MRS)

Principal Investigator: Professor David Gough

Host Institution: Institute of Education (now University College London)

Legacy Website: EPPI-Centre

Node Publications: Node Publications

The Methods for Research Synthesis (MRS) Programme developed methods for synthesising the results of all types of research and applies these methods to substantive review topics across the social sciences.

Methods include statistical meta analysis of quantitative data, conceptual synthesis of qualitative research findings, combining quantitative and qualitative research and the analysis of non-research data, such as patient information leaflets (Methods for Systematic Information Synthesis).

MRS developed rigorous, explicit, accountable and transparent methods across the whole range of research questions and for all types of evidence and apply these methods to substantive review topics. Most methods development has been on synthesis of numerical data (such as statistical meta analysis) and synthesis of qualitative data (such as meta ethnography.) In order to help develop a broader range of fit-for-purpose methods of synthesis MRS developed a framework to describe the full range of questions asked by social science research.


Real Life Methods (RLM)

Principal Investigator: Professor Jennifer Mason

Host Institutions: University of Manchester, University of Leeds

Node Publications: Node Publications

Real Life Methods explored new research methods that aim to grasp the multidimensionality of “real lives”. Real Life Methods aimed their research to be able to reflect, describe and explain people’s everyday lives. They used innovative approaches and combinations of methods to give us new perspectives on significant research questions in the areas of family, youth and community.

Real Life Methods research programme was made up of four projects. Each project used a combination of methodological approaches to investigate its research questions. The methods chosen varied widely. They could be well-established (semi-structured interviews), recently-emerging (self-portraits, video diaries, visual ethnographies, walking interviews) or new (a qualitative “experiment”). They could be qualitative or quantitative, though their particular focus was on qualitatively-driven research. Real Life Methods used an “interdisciplinary” mix of methods, as their team was interdisciplinary and they explored how using methods associated with different social science disciplines can shape and enhance our research.



Principal Investigator: Professor Amanda Coffey

Host Institution: Cardiff University

Node Publications: Node Publications

Qualiti focused 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 included:

  • Exploiting new opportunities for the recording, display and communication of qualitative data
  • Exploring the opportunities and challenges for integrating different qualitative research approaches, modes of data collection, data types and analytical strategies
  • Developing innovative and participatory methods of qualitative inquiry
  • Enhancing the role, impact and understanding of qualitative inquiry in the public domain

Researchers at Qualiti were engaged in projects that developed the capacity for methodological innovation, integration and impact in the context of substantive research settings. Their demonstrator projects sought ways of actively engaging research users, participants and stakeholders in methodological advancement, developing and implementing innovative research practice, and informed their training and capacity building agenda.