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Conference organisers

 

Fiona Steele

Professor in Statistics

LSE
Email: f.a.steele@lse.ac.uk|

 

Paul Clarke

Professor of Social Statistics

University of Essex

Email: pclarke@essex.ac.uk|

 

 

Administration support and general enquiries

 

Ian Marshall

Research Administrator

LSE

Tel: +44 (0)20 7955 7511

Emil: i.marshall@lse.ac.uk|

 

Methods for Longitudinal Data Analysis in the Social Sciences

Monday 8 September 2014, 10:00 – 18:00
Followed by drinks reception and buffet dinner

Conference venue: New Theatre, East Building, Houghton Street, LSE campus


*** Limited additional places are now available to attend this conference. Please email Ian Marshall| if you would like to reserve a place. ***


These are unprecedented times for the social sciences in terms of the availability of high-quality longitudinal data. The richness of these data are enabling researchers to broaden their horizons and contemplate addressing research questions of increasing complexity, and develop models of increasing sophistication to answer these questions.  In this event, we bring together researchers from social statistics, biostatistics and economics to talk about some of the latest developments in this area.  The speakers will talk on a range of subjects, from innovative ways of collecting longitudinal data to dealing with its most difficult problems, from modelling growth and over-dispersion to estimating causal effects.  

This event is sponsored by the LEMMA node of the ESRC National Centre of Research Methods|, and is organised by Fiona Steele| (LSE) and Paul Clarke| (University of Essex).

Speakers

Paul Clarke| (University of Essex) 
Dynamic panel-data modelling with structural nested mean models

Marcel Das| (CentERdata / Tilburg University)
Innovation in online longitudinal data collection for scientific research

Bianca De Stavola| (London School of Hygiene and Tropical Medicine)
Mediation and life course epidemiology: Challenges and examples

Harvey Goldstein| (University of Bristol)
Modelling repeated measures growth data by aligning significant growth events and modelling changes in within-individual variability over time

Geert Molenberghs| (Katholieke Universiteit Leuven)
A flexible modelling framework for over-dispersed, hierarchical data of a joint nature

Anders Skrondal| (Norwegian Institute of Public Health)
Protective estimation of panel models when data are not missing at random

Tom Snijders| (University of Oxford, University of Groningen)
Longitudinal methods for using panel data of networks and behaviour to assess peer influence 

Please view abstracts of the talks HERE|


About the LEMMA project

The LEMMA (Longitudinal Effects, Multilevel Models and Applications) 3 project is a node in the third phase of the ESRC 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, which were concerned with the development of multilevel models for hierarchical and non-hierarchical data structures.

The overarching objective of LEMMA 3 is to build capacity in the analysis of longitudinal data. LEMMA 3 has four interrelated elements:

  • Statistical methods. Review and synthesis of important developments in longitudinal data analysis in biostatistics and econometrics, and development of new methods to better represent and understand social processes.
  • Statistical software. Implementation of new methods in the Stat-JR software environment.
  • Substantive research. Application of new methods to address a range of important social science questions, in collaboration with experts from medical sociology, health psychology, economics, education and developmental psychology.
  • Capacity building. Provide training in methods for the analysis of longitudinal and other multilevel data structures through face-to-face courses and online modules in the LEMMA virtual learning environment.

http://bristol.ac.uk/cmm/research/lemma/|

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