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7 - Studying processes: some methodological considerations

Published online by Cambridge University Press:  22 September 2009

Lea Pulkkinen
Affiliation:
University of Jyväskylä, Finland
Avshalom Caspi
Affiliation:
Institute of Psychiatry, London
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Summary

The purpose of this chapter is to discuss different approaches for studying processes. Since methods are – or at least should be – intimately related to the theory guiding the research it is natural to start from a meta theoretical perspective. A powerful general theoretical framework for studying personality in a life-course perspective is provided by the holistic-interactionistic research paradigm as incorporated in the new developmental science. Therefore, the chapter starts with a brief introduction of this framework and how it leads to an interest in studying processes. A very thought-provoking and potentially attractive approach to studying processes is given by emerging methods for studying nonlinear dynamical systems (NOLIDS). Some general ideas in NOLIDS are indicated and a few examples given of key concepts that seem relevant in relation to the study of personality. Against this background, the emphasis in current research on what will here be called static statistical methods is questioned and a number of approaches are discussed which stay closer to the process characteristics of the phenomena under study.

The issues treated in this chapter, although methodological and apart from the substantive issues treated elsewhere in this book, may be useful to consider in conjunction with the rest of the book.

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Paths to Successful Development
Personality in the Life Course
, pp. 177 - 200
Publisher: Cambridge University Press
Print publication year: 2002

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References

Abbott, A. (1995). Sequence analysis: new methods for old ideas. Annual Review of Sociology, 21, 93–113CrossRefGoogle Scholar
Abraham, F. D., and Gilgen, A. R. (eds.) (1995). Chaos theory in psychology. London: Praeger
Allport, G. (1937). Personality: A psychological interpretation. New York: Rinehart and Winston
Bailey, K. D. (1994). Typologies and taxonomies. New York, NY: Sage
Bartholomew, D. J. (1996). The statistical approach to social measurement. San Diego, CA: Academic Press
Barton, S. (1994). Chaos, self-organization, and psychology. American Psychologist, 49, 5–15CrossRefGoogle ScholarPubMed
Bereiter, C. (1963). Some persistent dilemmas in the measurement of change. In C. Harris (ed.), Problems in measuring change. Madison, WI: University of Wisconsin Press, 3–20
Bergman, L. R. (1988a). Modeling reality: some comments. In M. Rutter (ed.), Studies of psychosocial risk. The power of longitudinal data. Cambridge University Press, 354–66
Bergman, L. R. (1988b). You can't classify all of the people all of the time. Multivariate Behavioral Research, 23, 425–41CrossRefGoogle Scholar
Bergman, L. R. (1993). Some methodological issues in longitudinal research: looking ahead. In D. Magnusson and P. Casaer (eds.), Longitudinal research on individual development: Present status and future perspectives. Cambridge University Press, 217–41CrossRef
Bergman, L. R. (1995). Describing individual development using i-state sequence analysis (ISSA). Reports from the Department of Psychology, Stockholm University, no. 805
Bergman, L. R. (1998). A pattern-oriented approach to studying individual development: snapshots and processes. In R. B. Cairns, L. R. Bergman, and J. Kagan (eds.), Methods and models for studying the individual Thousand Oaks, CA: Sage, 83–121
Bergman, L. R. (2000). The application of a person-oriented approach: types and clusters. In L. R. Bergman, R. Cairns, L-G Nilsson, and L. Nystedt (eds.), Developmental science and the holistic approach. Mahwah, NJ: Erlbaum, 137–54
Bergman, L. R. (2001). A person approach in research on adolescence: some methodological challenges. Journal of Adolescent Research, 16, 28–53CrossRefGoogle Scholar
Bergman, L. R., and El-Khouri, B. M. (1999). Studying individual patterns of development using I-states as objects analysis (ISOA). Biometrical Journal, 41, 753–703.0.CO;2-K>CrossRefGoogle Scholar
Bergman, L. R., and Magnusson, D. (1991). Stability and change in patterns of extrinsic adjustment problems. In D. Magnusson, L. R. Bergman, G. Rudinger, and B. Törestad, (eds.) Problems and methods in longitudinal research. Cambridge University Press, 323–45CrossRef
Bergman, L. R., and Magnusson, D. (1997). A person-oriented approach in research on developmental psychopathology. Development and Psychopathology, 9, 291–319CrossRefGoogle ScholarPubMed
Berliner, L. M. (1992). Statistics, probability and chaos. Statistical Science, 7, 69–90CrossRefGoogle Scholar
Blashfield, R. K. (1980). The growth of cluster analysis: Tryon, Ward and Johnson. Multivariate Behavioral Research, 15, 439–58CrossRefGoogle ScholarPubMed
Block, J. (1971). Lives through time. Berkeley, CA: Bancroft Books
Block, J. (2000). Three tasks for personality psychology. In L. R. Bergman, R. Cairns, L-G Nilsson, and L. Nystedt (eds.), Developmental science and the holistic approach. Mahwah, NJ: Erlbaum, 155–64
Boker, S. M., and Graham, J. (1998). A dynamic systems analysis of adolescent substance use. Multivariate Behavioral Research, 33, 479–507CrossRefGoogle Scholar
Boker, S. M., and Nesselroade, J. (1998). A method for modeling the intrinsic dynamics of intraindividual variability: Recovering the parameters of simulated oscillators in multi-wave panel data. Unpublished manuscript
Breckenridge, J. N. (1989). Replicating cluster analysis: method, consistency and validity. Multivariate Behavioral Research, 24, 147–61CrossRefGoogle ScholarPubMed
Brown, C. (1995). Chaos and catastrophe theories. Quantitative Applications in the Social Sciences, 107. Thousand Oaks, CA: SageCrossRef
Cairns, R. B. (1986). Phenomena lost: issues in the study of development. In J. Valsiner (ed.), The individual subject and scientific psychology. New York: Plenum, 79–112CrossRef
Cairns, R. B., Elder, G. H. Jr, and Costello, E. J. (eds.) (1996). Developmental science. Cambridge University Press
Cairns, R. B., and Rodkin, P. C. (1998). Phenomena regained: from configurations to pathways. In R. B. Cairns, L. R. Bergman, and J. Kagan (eds.), Methods and models for studying the individual. Thousand Oaks, CA: Sage, 245–64
Casti, J. L. (1989). Alternate realities. Mathematical models of nature and man. New York, NY: Wiley
Cattell, R. B. (1957). Personality and motivation structure and measurement. New York, NY: World Books
Cronbach, L. J. (1975). Beyond the two disciplines of scientific psychology. American Psychologist, 30, 116–27CrossRefGoogle Scholar
Edelbrock, C. (1979). Mixture model tests of hierarchical clustering algorithms. The problem of classifying everybody. Multivariate Behavioral Research, 14, 367–84CrossRefGoogle ScholarPubMed
Gangestad, S., and Snyder, M. (1985). To carve nature at its joints: on the existence of discrete classes in personality. Psychological Review, 92, 317–49CrossRefGoogle Scholar
Giele, J. Z., and Elder, G. H. Jr, (eds.). (1998). Methods of life course research. Thousand Oaks, CA: Sage
Gleick, J. (1987). Chaos. Making a new science. New York, NY: Viking Press
Gustafson, S. B., and Ritzer, D. R. (1995). The dark side of normal: a psychopathy-linked pattern called aberrant self-promotion. European Journal of Personality, 9, 147–83CrossRefGoogle Scholar
Jackson, A. E. (1989). Perspectives on nonlinear dynamics, Cambridge University Press, vol. 1
James, L. R. (1998). Measurement of personality via conditional reasoning. Organizational Research Methods, 1 (2), 131–63CrossRefGoogle Scholar
Kelso, J. A. S. (1995). Dynamic patterns: the self-organization of brain and behavior. Cambridge, MA: The MIT Press
Kelso, J. A. S. (2000). Principles of dynamic pattern formation and changes in human behavior. In L. R. Bergman, R. Cairns, L-G Nilsson, and L. Nystedt (eds.), Developmental science and the holistic approach. Mahwah, NJ: Erlbaum, 63–83
Kelso, J. A. S., Ding, M., and Schöner, G. (1993). Dynamic pattern formation: a primer. In L. B. Smith and E. Thelen (eds.), A dynamic systems approach to development. Cambridge, MA: The MIT Press
Kliegl, R., and Baltes, P. B. (1987). Theory-guided analysis of development and aging mechanisms through testing-the-limits and research on expertise. In C. Schooler and K. W. Schaie (eds.), Cognitive functioning and social structure over the life course. Norwoord, NJ: Ablex, 95–119
Krauth, J., and Lienert, G. A. (1982). Fundamentals and modifications of configural frequency analysis (CFA). Interdisciplinaria, 3, (1)
Lewin, K. (1935). A dynamic theory of personality. New York, NY: McGraw-Hill
Lindsay, R. M., and Ehrenberg, A. S. C. (1993). The design of replicated studies. American Statistician, 43, 217–28Google Scholar
Lykken, D. T. (1991). What's wrong with psychology anyway? In D. Cicchetti and W. M. Grove (eds.), Thinking clearly about psychology (vol. 1). Minneapolis, MN: University of Minnesota Press
Magnusson, D. (1985). Implications of an interactional paradigm for research on human development. International Journal of Behavioral Development, 8, 115–37CrossRefGoogle Scholar
Magnusson, D. (1992). Back to the phenomena: theory, methods and statistics in psychological research. European Journal of Personality, 6, 1–14CrossRefGoogle Scholar
Magnusson, D. (ed.) (1996). The life-span development of individuals: Behavioral, neurobiological and psychosocial perspectives. A synthesis. Cambridge University Press
Magnusson, D. (1998). The logic and implications of a person approach. In R. B. Cairns, L. R. Bergman, and J. Kagan (eds.), Methods and models for studying the individual. Thousand Oaks, CA: Sage, 33–63
Magnusson, D. (1999). Holistic interactionism: a theoretical framework. In L. A. Pervin and O. P. John (eds.), Handbook of personality: Theory and research (2nd edn.). New York, NY: Guilford Press, 219–47
Magnusson, D., and Allen, V. L. (1983). Implications and applications of an interactional perspective for human development. In D. Magnusson and V. L. Allen (eds.), Human development: An interactional perspective. New York: Academic Press, 369–87
Magnusson, D., Bergman, L. R., Rudinger, G., and Törestad, B. (eds.) (1991). Problems and methods in longitudinal research: Stability and change. Cambridge University Press
McArdle, J. J. (1995). A statistical vector field analysis of longitudinal aging data, Experimental Aging Research, 21, 77–93Google Scholar
Meehl, P. E. (1990). Appraising and amending theories: the strategy of Lakatosian defense and two principles that warrant it. Psychological Inquiry, 1, 108–41CrossRefGoogle Scholar
Nesselroade, J. R., and Ghisletta, P. (2000). Beyond static concepts in modeling behavior. In L. R. Bergman, R. Cairns, L-G Nilsson, and L. Nystedt (eds.), Developmental science and the holistic approach. Mahwah, NJ: Erlbaum, 121–35
Nowak, A., and Lewenstein, M. (1994). Dynamical systems: a tool for social psychology? In R. R. Vallacher and A. Nowak (eds.), Dynamical systems in social psychology. San Diego, CA: Academic Press
Ott, E. (1993). Chaos in dynamical systems. Cambridge University Press
Pervin, L. A. (1989). Psychodynamic-systems reflections on a social intelligence model of personality. Advances in Social Cognition, 2, 153–61Google Scholar
Poincaré, H. (1946). The foundations of science. Lancaster, UK: The Science Press
Pulkkinen, L. (1996). Female and male personality styles: a typological and developmental analysis. Journal of Personality and Social Psychology, 70, 1288–306CrossRefGoogle ScholarPubMed
Richters, J. E. (1997). The Hubble hypothesis and the developmentalist's dilemma. Development and Psychopathology, 9, 193–229CrossRefGoogle ScholarPubMed
Robins, R. W., John, O. P., and Caspi, A. (1998). The typological approach to studying personality. In R. B. Cairns, L. R. Bergman, and J. Kagan (eds.), Methods and models for studying the individual. Thousand Oaks, CA: Sage, 135–8
Rogosa, D., and Willett, J. B. (1985). Understanding correlates of change by modeling individual differences in growth. Psychometrika, 50, 203–28CrossRefGoogle Scholar
Rutter, M. (1996). Developmental psychopathology as an organizing research concept. In D. Magnusson (ed.), The life-span development of individuals: Behavioral, neurobiological, and psychosocial perspectives. A synthesis. Cambridge University Press, 394–413
Rutter, M., and Pickles, A. (1990). Improving the quality of psychiatric data: classification, cause, and course. In D. Magnusson and L. R. Bergman (eds.), Data quality in longitudinal research. Cambridge University Press, 32–57
Schmitz, B. (1990). Univariate and multivariate time-series models: the analysis of intraindividual variability and intraindividual relationships. In A. von Eye (ed.), Statistical methods in longitudinal research. vol. Ⅱ: Time series and categorical longitudinal data. San Diego, CA: Academic Press, 351–86
Smith, L. B., and Thelen, E. (1993). A dynamic systems approach to development. Applications. Cambridge, MA: The MIT Press
Sorensen, A. B. (1998). Statistical models and mechanisms of social processes. Paper prepared for presentation at the conference on “Statistical issues in the social sciences”, Swedish Academy of Sciences, Stockholm, Sweden, 1–3 October, 1998
Stern, W. (1911). Die Differentielle Psychologie in ihren metodischen Grundlagen (Methodological foundations of differential psychology). Leipzig, Germany: Barth
Thelen, E. (1995). Motor development: a new synthesis. American Psychologist, 50, 79–95CrossRefGoogle ScholarPubMed
Vallacher, R. B., and Nowak, A. (1994). Dynamical systems in social psychology. San Diego, CA: Academic Press
Valsiner, J. (1984). Two alternative epistemological frameworks in psychology: the typological and variational modes of thinking. Journal of Mind and Behavior, 5, 449–70Google Scholar
Eenwyk, J. R. (1991). Archetypes: The strange attractors of the psyche. Journal of Analytical Psychology, 36, 1–25CrossRefGoogle Scholar
von Eye, A. (1990). Configural frequency analysis of longitudinal multivariate responses. In A. von Eye (ed.), Statistical methods in longitudinal research, vol. 2. New York, NY: Academic Press
Waller, N. G., and Meehl, P. E. (1998). Multivariate taxometric procedures. Distinguishing types from continua. Thousand Oaks, CA: Sage
Wikman, A. (1991). Att utveckla sociala indikatorer. (To develop social indicators.) Urval, No. 21. Stockholm Statistiska Centralbyrån
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