LEMMA 3: Longitudinal Effects, Multilevel Modelling and Applications

Project Details


LEMMA 3 is a node in the second phase of the ESRC-funded National Centre for Research Methods (NCRM). The mission of NCRM is to provide a strategic focal point for the identification, development and delivery of an integrated national research, training and capacity-building programme. The project builds on the work of LEMMA 1 and LEMMA 2.

Social science is all about understanding complex social processes that develop over time. For example, the processes through which people from families with differing socio-economic backgrounds end up with markedly different life outcomes. It has long been recognised that understanding such processes requires longitudinal data comprising repeated measurements of the key factors over time, and there has been substantial investment in the collection of such data.

The overarching objective of LEMMA 3 is to build capacity in the analysis of longitudinal data. LEMMA 3 aims to:

(1) Review and synthesise important developments in longitudinal data analysis;

(2) Develop and adapt new methodology that addresses important problems in social research today;

(3) Apply the newly developed methods to substantive research projects in collaboration with experts from medical sociology, health psychology, economics, education and developmental psychology;

(4) Implement the methodological research in the e-STAT software environment. e-STAT has been developed to overcome one of the biggest barriers facing social researchers, namely, learning to use statistical software packages.

Under LEMMA 3 (and its predecessors LEMMA 1 and 2) an unrestricted version of the MLwiN software is freely available to UK academics. The REALCOM and REALCOM-Impute software is freely available to all.

Finally, a collaborative project between LEMMA 3 and the PATHWAYS node of the NCRM aims to develop eBooks for causal modelling and missing data methods.
Effective start/end date1/10/1130/09/14

Structured keywords

  • SoE Centre for Multilevel Modelling
  • Jean Golding


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