Abstract
This is a response to the presentation by Wohlwill (this volume). To begin, I must admit that I have been a follower of Wohlwill’s research for a long time. In particular my own research has benefited from Wohlwill’s classic work on The age variable in psychological research (see Wohlwill, 1970, 1973). His current paper adds clarity and force to these issues so here I continue my enthusiastic support of Wohlwill’s work.
I have enjoyed the benefit of discussions about these ideas with many colleagues. I [hank Jack Wohlwill for his support of my work. This research has been supported by grants from the National Institute on Aging (AG07137).
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Arminger, G. (1986). Linear stochastic differential equation models for panel data with unobserved variables. In N. B. Tuma (Ed.), Sociological Methodology, 16, 187–213.
Baltes, P. B. (1987). Theoretical propositions of life-span developmental psychology: On the dynamics between growth and decline. Developmental Psychology, 23(5), 611–626.
Baltes, P. B., Reese, H. W., & Nesselroade, J. R. (1988). Introduction to research methods: Life span development psychology. Hillsdale, NJ: Erlbaum.
Blalock, H. M. (1985). Causal models in panel and experimental designs. New York: Aldine Publishers.
Cattell, R. B. (1966). Handbook of multivariate experimental psychology. New York: Rand McNally.
Cattell, R. B. (1982). Personality and learning theory. New York: Rand McNally.
Featherman, D. L., & Peterson, T. (1986). Markers of aging: Modeling the clocks that time us. Research on Aging 8(3), 339–365).
Geweke, J., & Singleton, K. (1981). Maximum likelihood confirmatory factor analysis of economic time series. International Economic Review, 22, 37–54.
Griffiths, D., & Sandland, R. (1984). Fitting generalized allometric models to multivariate growth data. Biometrics, 40, 139–150.
Horn, J. L. (1972). State, trait and change dimensions of intelligence. The British Journal of Educational Psychology, 42(2), 159–185.
Horn, J. L., McArdle, J. J., & Mason, R. (1983). When is invariance not invariant: A practical scientist’s look at the ethereal concept of factor invariance. The Southern Psychologist, 1(4), 179–188.
Humphreys, M. S., & Revelle, W. (1984). Personality, motivation and performance: A theory of the relationship between individual differences and information processing. Psychological Review, 91(2), 153–184.
Jones, M. B. (1962). Practice as a process of simplification. Psychological Review, 69(4), 274–294.
Jöreskog, K. G. (1970). Estimation and testing of simplex models. British Journal of Mathematical and Statistical Psychology, 23, 121–146.
Jöreskog, K. G., & Sörbom, D. (1979). Advances in factor analysis and structural equation models. Cambridge, MA: Abt Books.
Kearsley, G. P., Buss, A. R., & Royce, J. R. (1977). Developmental change and the multidimensional cognitive system. Intelligence, 1, 257–273.
Keats, J. A. (1983). Ability measures and theories of cognitive development. In H. Wainer & S. Messick (Eds.), Principals of modern psychological measurement: A festschrift for Frederic M. Lord (pp. 81–101). Hillsdale, NJ: Erlbaum.
Kessler, R. G, & Greenberg, D. F. (1981). Linear panel analysis: Models of quantitative change. New York: Academic Press.
Loehlin, J. C. (1987). Latent variable models: An introduction to factor, path, and structural analysis. Hillsdale, NJ: Erlbaum.
May, R. M. (1981). Theoretical ecology: principles and applications. Sunderland, MA: Sinauer Associates.
McArdle, J. J. (1986) Latent variable growth within behavior genetic models Behavior Genetics, 16(1), 163–200.
McArdle, J. J. (1988a). Dynamic but structural equation modeling of repeated measures data. In J. R. Nesselroade & R. B. Cattell (Eds.), The handbook of multivariate experimental psychology (Vol. 2. pp. 561–614). New York: Plenum Press.
McArdle, J. J. (1988b). Structural modeling experiments using multiple growth curves. In P. Ackerman, R. Kanfer, & R. Cudeck (Eds.), Learning and individual differences: Abilities, motivation, and methodology. Hillsdale, NJ: Erlbaum.
McArdle, J. J., Anderson, E., & Aber, M. S. (1987). Convergence hypotheses modeled and tested with linear structural equations. Proceedings of the National Center for Health Statistics Conference (pp. 351–357), NCHS, Hyattsville, MD.
McArdle, J. J., & Epstein, D. (1987). Latent growth curves within developmental structural equation models. Child Development, 58(1), 110–133.
McDonald, R. P. (1985). Factor analysis and related methods. Hillsdale, NJ: Erlbaum.
Meredith, W., & Tisak, J. (1984). Tuckerizing curves. Paper presented at the Annual Meetings of the Psychometric Society, Santa Barbara, CA (submitted for publication.
Molenaar, P. C. M. (1985). A dynamic factor model for the analysis of multivariate time series. Psychometrika, 50(2), 181–202.
Neimark, E. D., & Estes, W. K. (1967). Stimulus sampling theory. San Francisco, CA: Holden-Day.
Nesselroade, J. R. (1983). Temporal selection and factor invariance in the study of development and change. Life-span Development & Behavior, 5, 59–87.
Nesselroade, J. R., & Ford, D. (1985). P-technique comes of age. Multivariate, replicated, single-subject designs for research on older subjects. Research on Aging, 7, 46–80.
Newtson, D., Hairfield, J., Bloomingdale, J., & Cutino, S. (1987). The structure of action and interaction. Social Cognition, 5(3), 197–237.
Ramsey, J. O. (1982). When the data are functions. Psychometrika, 47(4), 379–389.
Rogosa, D., & Willett, J. B. (1985). Understanding correlates of change by modeling individual differences in growth. Psychometrica, 50(2), 203–228.
Rozeboom, W. (1978). General linear dynamic analysis (GLDA). Department of Psychology, University of Alberta, Edmonton, Canada.
Tucker, L. R. (1966). Learning theory and multivariate experiment: Illustration by determination of parameters of generalized learning curves. In R. B. Cattell (Ed.), The handbook of multivariate experimental psychology (pp. 476–501). Chicago: Rand McNally.
Waber, D. P., Mann, M. B., Merola, J., & Moylan, P. M. (1985). Physical maturation rate and cognitive performance in early adolescence: A longitudinal examination. Developmental Psychology, 21(4), 666–681.
Wohlwill, J. F. (1970). The age variable in psychological research. Psychological Review, 77(1), 49–64.
Wohlwill, J. F. (1973). The study of behavioral development. New York: Academic Press.
Woodbury, M. A., & Manton, K. G. (1983). A mathematical model of physiological dynamics of aging and correlated selection. I. Theoretical development and critiques. Journal of Gerontology, 38(4), 398–405.
Wright, S. (1921). Correlation and causation. Journal of Agricultural Research, 20, 557–585.
Zeaman, D., & House, B. J. (1963). The role of attention in retardate discrimination learning. In N. R. Ellis (Ed.), Handbook of mental deficiency (pp. 155–223). New York: McGraw-Hill.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1991 Springer Science+Business Media New York
About this chapter
Cite this chapter
McArdle, J.J. (1991). Structural Models of Developmental Theory in Psychology. In: Van Geert, P., Mos, L.P. (eds) Annals of Theoretical Psychology. Annals of Theoretical Psychology, vol 7. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-3842-4_6
Download citation
DOI: https://doi.org/10.1007/978-1-4615-3842-4_6
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4613-6714-7
Online ISBN: 978-1-4615-3842-4
eBook Packages: Springer Book Archive