Re-counting crime: New methods to improve the accuracy of estimates of crime
Recounting crime is a research project funded by the ESRC Secondary Data Analysis Initiative. Our aim is to explore new statistical methods to help us improve the accuracy and precision of crime estimates.
Integrating research infrastructure for European expertise on inclusive growth from data to policy (InGRID- 2)
The objectives of the InGRID-2 project are to advance the integration and innovation of distributed social sciences research infrastructures (RI) on ‘poverty, living conditions and social policies’ as well as ‘working conditions, vulnerability and labour policies’.
InGRID-2 includes transnational on-site support and visits to research institutes including the Cathie Marsh Institute for Social Research at The University of Manchester. These visits support mutual learning, methodological support and discussions of innovations, and improve data services and facilities of comparative research. The focus areas are a) integrated and harmonised data, (b) links between policy and practice, and (c) indicator-building tools. Joint research activities are conducted in the focus areas and concentrate on extending data integrations, exploring new data linkage and sources, innovating microsimulation tools, improving comparative policy data, and investigating new high-quality indicators.
Theoretical sampling design options for a new birth cohort
Funded by an invited ESRC grant from January to July 2019, this research project investigated the use of accelerated longitudinal designs for a new birth cohort study in the UK comparing a range of options.
The deliverable is here.
Third Network for the Analysis of EU-SILC (Net-SILC3)
Funded by the Statistical Office of the European Union (Eurostat) and coordinated by Luxembourg Institute of Socio-Economic Research, this project seeks to address methodological and analytical questions that are of particular importance at this stage of the maturation of EU-SILC. It follows on from two previous projects on the EU-SILC.
Estimating and correcting for multiple types of measurement errors in longitudinal studies
This project will develop a new type of model to enable estimation of, and correction for, multiple types of errors in longitudinal data using latent variable modeling. This model will make it possible to estimate and correct simultaneously for:
- method effects (where the response scale used for the question biases answers);
- acquiescence (where respondents tend to agree to questions regardless of their content);
- social desirability (where respondents provide answers in ways that are considered socially desirable);
- cross-cultural effects (where measurement errors vary cross-culturally).
Enhancing the quality and utility of longitudinal data for educational research
Longitudinal surveys face many challenges, including high non-response rates and increasing data collection costs, which threaten the quality and utility of the collected data. The planned research focuses on strategies for overcoming these challenges while making extensive use of data from the National Educational Panel Survey (NEPS).
Bayesian Adaptive Survey Design Network (BADEN)
The network - funded by The Leverhulme Trust - gathers researchers from academia and national statistical offices and gives a strong impetus to theory development and practical implementation of adaptive survey designs.
Adaptive survey designs differentiate survey design features for different population subgroups based on auxiliary data about the sample obtained from frame data, registry data or paradata. The development of a Bayesian framework will allow the learning and constantly updating of key input parameters to these design.
Accounting for informative item nonresponse in biomarkers collected in longitudinal surveys (WP3)
The WP3 work package of the National Centre for Research Methods (NCRM) aims to research and develop methods for compensating for non-response in the collection of biomarkers in longitudinal surveys. Non-response can arise from attrition at the interview or nurse visit stage as well as at the stage when blood is collected. Each of the typologies of non-response are driven by different non-response mechanisms and may be informative. Auxiliary information that can be used to compensate for the missing data can cause other non-sampling errors, such as linkage error, that needs to be accounted for when undertaking biosocial research.
Data without boundaries
The Data without boundaries project exists to support equal and easy access to official microdata for the European Research Area, within a structured framework where responsibilities and liability are equally shared.
The InGRID project is funded by the European Union’s Seventh Framework Programme for Research, Technological Development and Demonstration under Grant Agreement No 312691 and involves 17 European partners. Referring to the EU2020-ambition of Inclusive Growth, the general objectives of InGrid – Inclusive Growth Research Infrastructure Diffusion – are to integrate and to innovate existing, but distributed European social sciences research infrastructures on ‘Poverty and Living Conditions’ and ‘Working Conditions and Vulnerability’ by providing transnational data access, organising mutual knowledge exchange activities and improving methods and tools for comparative research.