Secondary data analysis: An introduction to cross-study research

Abstract: New to longitudinal data and don’t know where to start? Not sure how to clean and prepare datasets for your research? Curious about tips and best practices for managing and analysing large-scale secondary data? 

This workshop is designed to introduce you to the essentials of secondary data analysis. You’ll learn how to clean and prepare datasets, and how to effectively use, report, and interpret outputs of analysis, with a focus on longitudinal cohort study data. The UK is home to some of the world’s largest and longest-running longitudinal population studies, and this workshop will guide you in leveraging these rich data sources for your research in social sciences, epidemiology, and health studies. 

The workshop begins by demonstrating how to find datasets relevant to your research, followed by a step-by-step guide on downloading datasets, merging files and transforming data for analysis. You’ll discover best practices for preparing and cleaning data, using syntax, and file management to facilitate reproducibility and tackle common challenges in longitudinal research. The workshop involves a combination of interactive lectures and hands-on exercises using examples from the Millennium Cohort Study (MCS) to guide you through the whole process of getting started with real-world study data. In the workshop, you’ll gain practical experience in accessing and downloading secondary datasets, preparing data for analysis, running basic analysis in Stata, and exporting outputs into Microsoft programs. By the conclusion of the workshop, you’ll have acquired practical skills in working with real-world longitudinal data, from accessing datasets to conducting basic analyses and reporting results. You’ll be equipped with the knowledge needed to confidently use data from longitudinal population studies and integrate outputs into your dissertations, research papers, and publications. Prior experience with Stata and a foundational understanding of statistical techniques are recommended. 

Bio: Dr. Neil Kaye is a Senior Research Fellow at University College London, conducting research using longitudinal population studies. His interests lie in social inequalities, education policy, youth transitions, and the impact of multiple discrimination, with a focus on quantitative methodologies and social statistics. He joined CLOSER (the home of longitudinal research) in 2019 and leads its Education & Training strand, running workshops and creating online learning resources on the Learning Hub and Training Hub to increase the visibility and use of the main birth cohort and longitudinal population studies available in the UK.