The harmonisation of longitudinal data
A case study using data from cohort studies in The Netherlands and the United Kingdom
Bibliographic Data
| ID | 11198753 |
|---|---|
| Authors | Peter A Bath (0000-0002-6310-7396, University of Sheffield, corresponding author), Dorly Deeg (0000-0003-1131-6855, Vrije Universiteit Amsterdam), JAN POPPELAARS (Vrije Universiteit Amsterdam) |
| Year | 2010 |
| Volume | 30 |
| Issue | 8 |
| Pages | 1419-1437 |
| Publication date | 2010-11-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Ageing and Society (JOURNAL) |
| Journal identifiers | ISSN: 0144-686X • E-ISSN: 1469-1779 |
| Publisher | Cambridge University Press (CUP) (PUBLISHER) |
| DOI | 10.1017/s0144686x1000070x |
| OpenAlex | W2115971468 |
| Language | EN |
| Citations received | 8 |
| References cited | 19 |
This paper presents a case study of the challenges and requirements associated with harmonising data from two independently-conceived datasets from The Netherlands and the United Kingdom: the Longitudinal Aging Study Amsterdam (LASA) and the Nottingham Longitudinal Study of Activity and Ageing (NLSAA). The objectives were to create equivalent samples and variables, and to identify the methodological differences that affect the comparability of the samples. Data are available from the two studies' 1992–93 surveys for respondents born during 1908–20, and the common data set had 1,768 records and enabled the creation of 26 harmonised variables in the following domains: demographic composition and personal finances, physical health, mental health and loneliness, contacts with health services, physical activity, religious attendance and pet ownership. The ways in which the methodological differences between the two studies and their different selective attrition might lead to sample differences were carefully considered. It was concluded that the challenges of conducting cross-national comparative research using independent datasets include differences in sampling, study design, measurement instruments, response rates and selective attrition. To reach conclusions from any comparative study about substantive socio-cultural differences, these challenges must first be identified and addressed
Attendance · Attrition · Comparability · Geography · Loneliness · Longitudinal data · Longitudinal study · Political science · Sample (material) · Sociology · demographic modeling and climate adaptation · Demography · Health disparities and outcomes · Mathematics · Medicine · Migration, Aging, and Tourism Studies · Psychology · Social Psychology · Gerontology
Integrating prospective longitudinal data
Loneliness and Health in Older Adults
Association between Internet Usage and Quality of Life of Elderly People in England
Evaluating the harmonization potential of oral health‐related questionnaires in national longitudinal birth and child cohort surveys
Growing up Healthy in Families Across the Globe
A Nonparametric, Multiple Imputation-Based Method for the Retrospective Integration of Data Sets
The Anatomy of Developmental Predictors of Healthy Lives Study (TADPOHLS)
Methodological challenges in harmonisation of the variables used as indicators of social capital in epidemiological studies of ageing – results of the ATHLOS project
Integrative data analysis
“Mini-mental state”
The Hospital Anxiety and Depression Scale
The CES-D Scale
Northern European retired residents in nine southern European areas
Autonomy and well-being in the aging population
Old People in Three Industrial Societies
Living Arrangements and Social Networks of Older Adults
| Unique citing works | 8 |
|---|---|
| Citations per year | 0,67 |
| Citation span | 2014 - 2024 (11) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 7 |