Presentation on theme: "Introduction to longitudinal studies in the UK"— Presentation transcript:
1 Introduction to longitudinal studies in the UK Nick Buck,Institute for Social and Economic Research, University of Essex
2 Summary Overview of UK Longitudinal Studies Rationale for longitudinal research methodsIntroduction to the research contribution of longitudinal studiesTaxonomy of longitudinal studies
3 UK Longitudinal Studies UK portfolio is particularly rich. Around the world we can identify five main types of LS:Household Panel surveysBirth Cohort StudiesLongitudinal studies of ageingStudies of the transition from school to workCensus linkage and other admin based studiesThe UK almost unique in being well represented in all these.
4 UK Longitudinal Studies (2) Household Panel surveys: British Household Panel SurveyBirth Cohort Studies: National Child Development Study, Birth Cohort Study 1970, Millennium Cohort Study and moreLongitudinal studies of ageing: English Longitudinal Study of AgeingStudies of the transition from school to work: Youth Cohort Study, Longitudinal Study of Young People in EducationCensus linkage and other admin based studies: ONS Longitudinal Study, Scottish Longitudinal Study... plus others, e.g. Families and Children Survey, British Election Study, Wealth and Assets Survey
5 What are Longitudinal Studies? Most generally, longitudinal studies collect data about the same subjects relating to multiple time pointsSubjects may be individual people or other entities, e.g. organisations such as firms – but here mostly concerned with studies of peopleNormally LS restricted to studies which collect data at several times (contrast retrospective life history studies which collect data about multiple time points on single occasion).But LS often use retrospective methods
6 Why longitudinal research? Longitudinal research provides an understanding of social change, of the trajectories of individual life histories and of the dynamic processes that underlie social and economic life, not possible from research based on cross-sectional data.The recent development of LS in the UK has underpinned advances in social science method and in understanding of major social changes and policy interventionsWe can identify a range of issues and types of research where longitudinal seem especially appropriate.
7 Rationale for longitudinal research (1) Focus on change Longitudinal approaches are essential when phenomena of interest directly concerned with individual level change – time is part of the definition, e.g.:the dynamics of poverty,employment instability,social mobilitymost demographic events: births, marriage, divorce, death, migration
8 Rationale for longitudinal research (2) Investigating casual processes Use longitudinal approaches when want to infer causation from temporal ordering, e.g.:the effects of unemployment on mental healthof childhood circumstances on later life chances;Or to investigate effects of events,e.g. what happens to incomes of husbands and wives after divorce
9 Rationale for longitudinal research (3) Controlling for fixed characteristics Can use longitudinal methods to investigate associations where an unmeasured characteristic may affect the outcome, provided this can be assumed to be fixed over period of observationUse repeated measures data to model differences (i.e. if effect if B on A is contaminated by unmeasured C, can investigate effect of change in B on change in A, if C fixed).Examples of unmeasured fixed characteristics: ability, motivation, preferences.E.g. effects of wage rates on hours worked
10 Rationale for longitudinal research (4) Separating age, period and cohort It is hypothesized that a person’s characteristics, attitudes and behaviour, change as they get older, but also that cohorts will differ including both the effects of transmission from their parents, and period specific events experienced.Understanding social change of requires disentangling this – normally needing long period longitudinal data.E.g. are changing social norms with respect to marriage/cohabitation or gender roles a consequence of cohort succession, or all cohorts changing together?
11 Rationale for longitudinal research (5) (quasi-)experimental design Longitudinal methods often used to establish the effect of a ‘treatment’ in formal random control trailEstablished LS may also be used to assess policy effect e.g. impact of the introduction of public policy, (methods developed to deal with non-random selection into policy)LS may be able to take advantage of ‘natural experiments’ – e.g. devolution in UK government
12 Examples of Longitudinal Research Disentangling the effects on children of school and family background in order to understand social mobility and the effectiveness of educational interventions – and to identify the key points for intervention.Examining the effects of changing patterns of marriage, cohabitation and childbirth on the time children are likely to spend in lone parent families – and the effects on their later lives.Understanding the defining characteristics of people who experience repeated spells of unemployment and poverty – and their ‘scarring’ effects, which make it difficult for people to find work and/or escape poverty in the future.
13 Taxonomy of longitudinal studies Distinguish surveys from other types (e.g. using administrative data)Prospective (repeated surveys) versus retrospectiveKey dimensions of longitudinal study designResearch rationale for different designsMost surveys discussed here designed as longitudinal from the start – not always the case
14 Surveys versus administrative data Administrative data (collected for bureaucratic/management purposes) an alternative to the costly process of collecting sample surveysAdvantages of admin data:comprehensive coverage of clientele of admin agencyprovide authoritative statement of behaviour/circumstances related to the agency’s activities (eg benefit records)Problems:limitations on access and restrictive confidentiality requirementslimited scope of data (since limited to the agency’s own purposes)But the model in which admin records are used as the sampling frame for further survey activity, or supplement survey data may provide promise for the future.
15 Retrospective data as alternative to prospective data Advantages:Quick, in the sense that all the data arrives at the same time,and therefore cheap, requiring only a single measurement cycle (contrast prospectiverespondents’ narrative have internal consistencyDisadvantages:Recall errorInternal consistency may be a consequence of recall error and reinterpretationSubject to survivor bias – not everyone lives long enough to be interviewed.ProspectiveAdvantages:Higher quality of current reports over retrospectiveFull sample at start of processDisadvantages:Slow, since repeated measures take time to accumulate into a longitudinal narrativeCostly – repeated data collectionAttritionMeasurement error issues
16 Key dimensions of longitudinal study design Demarcation of population universe:Whole country/ smaller areaWhole age range/ particular cohortPopulation sub-group e.g. minority ethnic groupRelevant for particular programme/policyUnit of analysis: individual, family grouping, individual-in-household, organisationStudy duration: indefinite, whole life, planned fixed durationMeasurement frequency: fixed frequency, key life stages
17 Research aims of design Repeated measurement using same questions to establish rates of change and patterns of association over timeAssessment of rates of development through questions tailored to particular ages at different waves/sweepsAccumulation of life history data from multiple waves/sweepsPre- and post-intervention measurementRespondents’ own accounts of changeNB: individual studies combine several of these
18 Household Panel Surveys (e.g. BHPS) Universe: whole populationUnit of analysis: individual in householdStudy duration: indefiniteMeasurement interval: fixed, annualResearch aims of design: repeated measures, accumulation of life history dataMany international comparator studies: e.g. PSID, German SOEP
19 Birth Cohort Studies (e.g. NCDS, BCS70, MCS) Universe: sample of births from particular year (1958, 1970, )Unit of analysis: individual, with associated othersStudy duration: whole lifeMeasurement interval: key development points, then regular intervalsResearch aims of design: developmental measures, some repeated measures, accumulation of life history dataFew international comparator studies, but growing number around millennium
20 Ageing Studies (e.g. ELSA) Universe: whole population above e.g. 50 at time of sampling – possible refreshmentUnit of analysis: individual plus partnerStudy duration: whole lifeMeasurement interval: fixed, biennialResearch aims of design: repeated measures, accumulation of life history data (focus on measures of relevance to older population)International comparator studies in USA (HRS) and Europe (SHARE)
21 Youth Studies (e.g. YCS, LSYPE) Universe: individual school yearsUnit of analysis: individual plus data from e.g. parentsStudy duration: fixed planned duration, up to end of process under study; start new cohorts to replaceMeasurement interval: fixed, annualResearch aims of design: developmental measures, some repeated measuresLimited international comparator studies, e.g. NLSY in USA
22 Census link studies (e.g. LS, SLS) Universe: whole populationUnit of analysis: individual (some linked measures for household)Study duration: indefiniteMeasurement interval: census fixed, decennial, plus other continuous input sources - registrationResearch aims of design: repeated measures, accumulation of life history dataLimited international comparator studies
23 ConclusionThis presentation has shown the value and variety of longitudinal studiesNext presentation discusses individual studies in more detail – how to chose a particular study for research.