Intraindividual Variability in Development Within and Between Individuals
Abstract
A focus on the study of development and other kinds of changes in the whole individual has been one of the hallmarks of research by Magnusson and his colleagues. A number of different approaches emphasize this individual focus in their respective ways. This presentation focuses on intraindividual variability stemming from Cattell's P-technique factor analytic proposals, making several refinements to make it more tractable from a research design standpoint and more appropriate from a statistical analysis perspective. The associated methods make it possible to study intraindividual variability both within and between individuals. An empirical example is used to illustrate the procedure.
References
1977). Life-span developmental psychology: Introduction to research methods . Monterrey, CA: Brooks/Cole.
(1999). Studying individual patterns of development using i-states as objects analysis (ISOA). Biometrical Journal , 41, 753– 770.
(2001). in press A method for modeling the intrinsic dynamics of intraindividual variability: Recovering the parameters of simulated oscillators in multiwave data. Multivariate Behavioral Research ,.
(1994). A comparison of self-esteem lability and low trait self-esteem as vulnerability factors for depression. Journal of Personality and Social Psychology , 66, 166– 177.
(1998). Methods and models for studying the individual . Thousand Oaks, CA: Sage.
(1963). The structuring of change by P-technique and incremental R-technique. In C.W. Harris (Ed.), Problems in measuring change (pp. 167-198). Madison, WI: University of Wisconsin Press.
(1947). P-technique demonstrated in determining psychophysical source traits in a normal individual. Psychometrika , 12, 267– 288.
(1961). The meaning and measurement of neuroticism and anxiety . New York: Ronald Press.
(1997). Intra-individual variability in perceived control in an elderly sample: The MacArthur Successful Aging Studies. Psychology and Aging , 12, 489– 502.
(1981). A one-factor multivariate time series model of metropolitan wage rates. Journal of the American Statistical Association , 76, 774– 781.
(1981). Maximum likelihood “confirmatory” factor analysis of economic time series. International Economic Review , 22, 37– 54.
(1990). Variations in sex-related cognitive abilities across the menstrual cycle. Brain and Cognition , 14, 26– 43.
(1972). State, trait, and change dimensions of intelligence. The British Journal of Educational Psychology , 42, 159– 185.
(1990). Multivariate, replicated, single-subject designs and P-technique factor analysis: A selective review of the literature. Experimental Aging Research , 16, 171– 183.
(1978). Intraindividual differences dimensions of mood change during pregnancy identified in five P-technique factor analyses. Journal of Research in Personality , 12, 205– 224.
(1972). The contribution of P-technique to personality, psychotherapy, and psychosomatic research. In R.M. Dreger (Ed.), Multivariate personality research: Contributions to the understanding of personality in honor of Raymond B. Cattell (pp. 387-410). Baton Rouge, LA: Claitor's Publishing Division.
(1997). The logic and implications of a person approach. In R.B. Cairns, L.R. Bergman, & J. Kagan (Eds.), The individual as a focus in developmental research (pp. 33-62). New York: Sage.
(1982). Structural equation modeling of an individual system: Preliminary results from “A case study in episodic alcoholism.” . Unpublished manuscript, Department of Psychology, University of Denver.
(1985). A dynamic factor model for the analysis of multivariate time series. Psychometrika , 50, 181– 202.
(1997). Establishing a reference frame against which to chart age-related change. In M.A. Hardy (Ed.), Studying aging and social change: Conceptual and methodological issues (pp. 191-205). Thousand Oaks, CA: Sage.
(1985). P-technique comes of age: Multivariate, replicated, single-subject designs for research on older adults. Research on Aging , 7, 46– 80.
(2000). Beyond static concepts in modeling behavior. In L.R. Bergman & R.B. Cairns (Eds.), Developmental science and the holistic approach (pp. 121-135). Mahwah, NJ: Erlbaum.
(2001). Alternative dynamic factor models for multivariate time-series analyses. In D.M. Moskowitz & S.L. Hershberger (Eds.), Modeling intraindividual variability with repeated measures data: Advances and techniques. Mahwah, NJ: Erlbaum.
(1999). Pooling lagged covariance structures based on short, multivariate time-series for dynamic factor analysis. In R.H. Hoyle (Ed.), Statistical strategies for small sample research. Newbury Park, CA: Sage.
(1994). Intraindividual stability in the organization and patterning of behavior: Incorporating psychological situations into the idiographic analysis of behavior. Journal of Personality and Social Psychology , 67, 674– 687.
(1994). The study of intraindividual differences by means of dynamic factor models: Rationale, implementation, and interpretation. Psychological Bulletin , 116, 1 166– 186.
(1982). The structure of mood change: Idiographic/nomothetic analysis. Journal of Personality and Social Psychology , 43, 1 111– 122.
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