Data harmonisation

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Data harmonisation involves recoding or modifying variables so that they are comparable across research studies.

What does harmonising data involve and why is it important?

In order to make full use of the cohort and longitudinal studies that we have in the UK, we need to be able to make comparisons both within and across studies. Repeating the same longitudinal analysis across a number of studies allows researchers to test whether results are consistent across studies, or differ in response to changing social conditions.

Cross-cohort analysis helps us understand more about societal change and how changes in the policy environment impact on outcomes for individuals.

What are the challenges?

Different studies have used different methods to collect information on important aspects of respondents’ lives. For example, measures of household income and measures of some senses, such as vision, are collected in quite different ways both within the studies over time and crucially, across the separate studies.

What is CLOSER doing about it?

Under the data harmonisation work stream, CLOSER is currently working on the following projects:

Harmonising measures of body size and body composition

Harmonising measures of occupation and education

Harmonising earnings and income

Harmonising socio-economic status and qualifications in ALSPAC

Harmonising strategies for analysing biological samples

Harmonising measures of senses and behaviour

Prospective associations between childhood environment and adult mental wellbeing

Review of methods for determining pubertal status

Exploiting the existing biomarker data available in CLOSER

Overcrowding and health: Methodological innovation for socio-economic measure in longitudinal studies

Socioeconomic differentials in physical activity by age and cohort: enhancing the CLOSER cohort resource to inform research, policy and practice

Maximising the take up of mental health measures from UK cohorts and longitudinal studies

Scoping existing dietary data available in CLOSER to support cross-cohort research questions

The creation of a life course methylome through data harmonisation in CLOSER studies

Assessment and harmonisation of cognitive measures in British birth cohorts

Harmonisation of mental health measures in British birth cohorts