Theoretical and technical orientations toward longitudinal research in the social sciences

1. Theoretical and technical orientations toward longitudinal research in the social sciences Frans Willekens Workshop on Longitudinal Research in Social Sciences,London, Ont., Oct. 25-27, 1999

2. 1. Basic orientationsand basic issues

3. Life is a composite process that unfolds as the result of an interplay between person and setting Persons in similar situations are more likely to experience similar life courses than persons in different situations  cultures, generations, clusters Is universal

4. Processes ofhuman development • Biology (biodemography) • Cognition (learning, experience, socialisation) • Emotion Is universal

5. Cognitive processesInformation, knowledge • Knowledge is organised in cognitive schemes (schemas, frames, scripts) • Schemes are adapted to new demands (Piaget) • Assimilation: fitting information into cognitive scheme (how we interpret the world) • Accommodation: adjustment of scheme to accommodate discrepant information • Schemes are formed by social interaction(learning, social enforcement, etc.) • Schemes are intermediate between person and context (‘filter’)  necessary for understanding behaviour (e.g. orientation, expected outcome in value expectancy theory [prediction] )

6. Developmental process • Proceeds in stages: each stage holds the fruits of the past and the seeds of the future • Transitions are discontinuities, hence critical periods involving re-assessment, detachment, critical choices and attachment (adherence) The life course is a developmental process Demographic events are milestones in the lives of people, involving long-term commitments

7. Developmental process • Description: the study of development requires repeated measurements (longitudinal observation) • to identify what remains constant and what is changing (constancies amid change) • to determine the timing of changes, sequence of changes, and the rate of change  to determine structure of the process

8. Developmental process • Explanation: • Innate factors (personal characteristics, ‘endowments’, expectations/predictions) and contextual factors (contemporary and historical [lags]) • relation between developmental processes (stat. association) • Understanding: causal mechanisms (how, why) • Path dependence, cumulative causation • Processes internal to the system being studied Repeated measurements may be sufficient for description but inadequate for understanding (T. Boerma, 1996). Understanding requires the detection of underlying (internal) mechanisms.

9. Basic issues is life-course research • How do people organise their lives? • Lives are organised around life events (e.g. demographic events)  life structure • Adaptation (coping) • Planning (e.g. family planning; career planning; personal financial planning) • The occurrence and timing of events are affected by choice and chance • Choice theory (discrete choice, sequential choice, search) • Probability theory • Activities (careers) compete for scarce resources (time, energy)  (in)compatibility

10. Basic issues is life-course research • Time: conceptual and measurement issues • Conceptual issues • Chronological time: situates transitions on time scale • Developmental time: situates transitions in dev. Process • Process time, individual time • ‘Biological clock’ • ‘Developmental readiness’ • Parallel developmental processes: synchronisation • Social time: situates transitions in socially prescribed timetable (e.g. age norms; ‘social clock’) • ‘on time’, ‘late, early’ [life course as social construct].

11. Basic issues is life-course research • Time: conceptual and measurement issues • Measurement issues • Time at event  time at onset of process leading to event • External (objective) time  internal (subjective; perceived) time  recall bias (forgetting, telescoping, heaping, etc) • Simultaneity (events occurring simultaneously) • Fuzzy time (Courgeau and Lelièvre)

12. Basic issues is life-course research • Risk and uncertainty • Conceptual issues • Risk, uncertainty, surprise • Risk: event known, probability of event known • Uncertainty: event known, probability not known • Surprise: event not known, probability not known • Being at risk: exposure: probability of event is positive • Duration at risk • Risk level (susceptibility; high risk vs low risk) • Risk factor and risk indicators (epidemiology) • Measurement issues • Duration at risk: ‘observation window’, censoring • Risk levels: stratification, exposure analysis Risk assessment

13. 2. The life course: a useful organising principle

14. General shifts in social sciences • From structure to process • From macro to micro • From analysis to synthesis • From certainty to uncertainty

15. From structure to process • From structure: Classification/taxonomy/typology • To process (causal mechanism): • Structures are outcomes of processes • Changes in structures (events) are outcomes of processes • Process is complex because of: • Ontogenetic nature of process • Epigenetic nature of process (stages) • Teleological nature of process

16. From macro to micro • Coleman: modes of explanation: • System level • Processes internal to system: agents, actors • Methodological individualism • Complex processes can be understood in terms of elementary building blocks (processes, rules) • Theoretical models (Burch) • Micro-macro link: • Embeddedness: interactions between multilevel processes

17. From analysis to synthesis • Analysis: identify the relations and building blocks • Synthesis: reconstruct life histories using system of rules  microsimulation

18. From certainty to uncertainty • Events cannot be predicted with certainty • Probability theory - stochastic processes • Causality is probabilistic

19. 3. Anatomy of the life course Basic unit of analysis: events Events define stages (states)

20. Anatomy of the life course • State: attributes at t  multistate analysis • Domains of life • Event: change in attribute • Sequence of events and stages: career • Sets of parallel careers: life course (Elder) • Careers in ‘pure state’ • Careers in presence of other careers (disturbances) • Principle of conditional independence • Set of interdependent life courses: linked lives

21. 4. Life history models • Focus: state occupied • Focus: status change (events)

22. Prediction of state occupancies • Current state: binomial or multinomial model • Probability model: • Regression model: logit model / logistic regression

23. Prediction of state occupancies • Status at two points in time: Markov model and multistate model Pj(t+1) = i pij(t) Pi(t) • with pij(t) the transition probability determined by direct method or indirect method (occurrence-exposure rate)

24. Prediction of events • Occurrence: logit model • Number of occurrences: Poisson model • Rate of occurrence: log-rate model (o/e rate)

25. Life is a composite process that unfolds as the result of an interplay between person and setting Multiprocess and multilevel • Elementary processes arranged in sequence and parallel • Each process has beginning (onset), continuation (progession), and end (termination) • Multistate process