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Handbook of Community Psychology pp 697–723Cite as

Statistical Models for Change

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Abstract

Themes involving “change” recur in psychological research with great frequency. For example, the efficacy of social interventions and policy decisions is often measured in terms of whether change can be observed in whatever units are being assessed (e.g., people, classrooms, organizations; cf., Judd & Kenny, 1981). Lifespan developmental studies are often concerned with the “natural” or “historical” changes that occur either within or across individuals (e.g., Nesselroade, 1988). Finally, under some research circumstances, investigators are interested in differentiating change that occurs as a function of development from change that occurs as the result of some social intervention (e.g., research in developmental epidemiology; Kellam, 1990)

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References

  • Agresti, A. (1990).Categorical data analysisNew York: Wiley

    Google Scholar 

  • Allison, P. D. (1984).Event history analysisBeverly Hills: Sage

    Google Scholar 

  • Bank, L., Dishion, T. J., Skinner, M., & Patterson, G. R. (1990). Method variance in structural equation modeling: Living with the “glop.” In G. R. Patterson (Ed.)Depression and aggression in family interaction(pp. 247–279). Hillsdale, NJ: Erlbaum

    Google Scholar 

  • Bentler, P. M. (1978). The interdependence of theory, methodology, and empirical data: Causal modeling as an approach to construct validation. In D. B. Kandel (Ed.)Longitudinal research on drug use: Empirical findings and methodological issues(pp. 267–302). Washington, D.C.: Hemisphere

    Google Scholar 

  • Bentler, P. M. (1983). Some contributions to efficient statistics in structural models: Specification and estimation of moment structures.Psychometrika 48493–517

    Article  Google Scholar 

  • Bentler, P. M., & Woodward, J. A. (1978). A Head Start reevaluation: Positive effects are not yet demonstrable.Evaluation Quarterly2, 226–238

    Article  Google Scholar 

  • Bereiter, C. (1963). Some persisting dilemmas in the measurement of change. In C. W. Harris (Ed.)Problems in measuring change(pp. 3–20). Madison: University of Wisconsin Press

    Google Scholar 

  • Bishop, Y. M. M., Fienberg, S. E., & Holland, P. W. (1975).Discrete multivariate analysisCambridge, MA: MIT Press

    Google Scholar 

  • Bock, R. D. (Ed.). (1989).Multilevel analysis of educational dataSan Diego: Academic

    Google Scholar 

  • Bollen, K. A. (1989).Structural equations with latent variablesNew York: Wiley

    Google Scholar 

  • Browne, M. W. (1982). Covariance structures. In D. M. Hawkins (Ed.)Topics in applied multivariate analysis(pp. 72–141). Cambridge, England: Cambridge University Press

    Chapter  Google Scholar 

  • Bryk, A. D., & Raudenbush, S. W. (1987). Application of hierarchical linear models to assessing change.Psychological Bulletin 101147–158

    Article  Google Scholar 

  • Burchinal, M., & Appelbaum, M. I. (1991). Estimating individual developmental functions: Methods and their assumptions.Child Development 6223–43

    Article  Google Scholar 

  • Buss, A. R. (1979). Toward a unified framework for psychometric concepts in the multivariate developmental situation: Intraindividual change and inter-and intraindividual differences. In J. R. Nesselroade & P. B. Baltes (Eds.)Longitudinal research in the study of behavior and development(pp. 41–59). New York: Academic

    Google Scholar 

  • Campbell, D. T., & Erlebacher, A. (1975). How regression artifacts in quasi-experimental evaluations can mistakenly make compensatory education look harmful. In E. L. Struening & M. Guttentag (Eds.)Handbook of evaluation research Vol. 1(pp. 597–617). Beverly Hills: Sage

    Google Scholar 

  • Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validity by the multitrait-multimethod matrix.Psychological Bulletin 5681–105

    Article  PubMed  Google Scholar 

  • Cattell, R. B. (1966). Patterns of change: Measurement in relation to state-dimension, trait change, lability, and process concepts. In R. B. Cattell (Ed.)Handbook of multivariate experimental psychology(pp. 355–402). Chicago: Rand McNally

    Google Scholar 

  • Cattell, R. B. (1988). The data box: Its ordering of total resources in terms of possible relational systems. In J. R. Nesselroade & R. B. Cattell (Eds.)Handbook of multivariate experimental psychology(2nd ed., pp. 69–130). New York: Plenum

    Chapter  Google Scholar 

  • Cohen, J., & Cohen, P. (1983).Applied multiple regression/correlation for the behavioral sciences(2nd ed.). Hillsdale, NJ: Erlbaum

    Google Scholar 

  • Collins, L. M., & Horn, J. L. (Eds.). (1991).Best methods for analyzing changeWashington, D.C.: APA Publications

    Google Scholar 

  • Collins, L. M., & Cliff, N. (1985). Axiomatic foundations of a three-set Guttman simplex model with applicability to longitudinal data.Psychometrika 50147–158

    Article  Google Scholar 

  • Comrey, A. L. (1973).A first course in factor analysisNew York: Academic

    Google Scholar 

  • Cook, T. D., & Campbell, D. T. (1979).Quasi-experimentation: Design and analysis issues for field settingsChicago: Rand McNally

    Google Scholar 

  • Cronbach, L. J., & Furby, L. (1970). How should we measure “change” -or should we?Psychological Bulletin 7468–80

    Article  Google Scholar 

  • Cronbach, L. J.&Meehl, P. F. (1955). Construct validity in psychological tests.Psychological Bulletin 52281–302

    Article  PubMed  Google Scholar 

  • Elandt-Johnson, R. C., & Johnson, N. L. (1980).Survival models and data analysisNew York: Wiley

    Google Scholar 

  • Falk, R. F., & Miller, N. B. (1991). A soft models approach to family transitions. In P. A. Cowan & M. Heatherington (Eds.)Family transitions(pp. 273–301). Hillsdale, NJ: Erlbaum

    Google Scholar 

  • Fiske, S. T., & Pavelchak, M. A. (1986). Category-based versus piecemeal-based affective responses: Developments in schema-triggered affect. In R. M. Sorrentino & E. T. Higgins (Eds.)Handbook of motivation and cognition(pp. 167–203). New York: Guilford

    Google Scholar 

  • Goldstein, H. (1979).The design and analysis of longitudinal studiesLondon: Academic

    Google Scholar 

  • Golembiewski, R. T., Billingsley, K., & Yeager, S. (1976). Measuring change and persistence in human affairs: Types of change generated by OD designs.Journal of Applied Behavioral Science 12133–157

    Article  Google Scholar 

  • Gollob, H. F.&Reichardt, C. S. (1987). Taking account of time lags in causal models.Child Development 5880–92

    Article  PubMed  Google Scholar 

  • Gottman, J. M. (1981).Time-series analysis: A comprehensive introduction for social scientistsNew York: Cambridge University Press

    Google Scholar 

  • Gottman, J. M., & Roy, A. K. (1990).Sequential analysisCambridge, England: Cambridge University Press. Harris, C. W. (Ed.). (1963).Problems in measuring changeMadison: University of Wisconsin Press

    Google Scholar 

  • Harris, R. J. (1983). Aprimer of multivariate statistics(2nd ed.). New York: Academic

    Google Scholar 

  • Hertzog, C., & Nesselroade, J. R. (1987). Beyond autoregressive models: Some implications of the trait-state distinction for the structural modeling of developmental change.Child Development 5893–109

    Article  PubMed  Google Scholar 

  • Hooker, K., Nesselroade, D. W., Nesselroade, J. R., & Lerner, R. M. (1987). The structure of intraindividual temperament in the context of mother-child dyads: P-technique factor analyses of short-term change.Developmental Psychology 23332–346

    Article  Google Scholar 

  • Houts, A. C., Cook, T. D., & Shadish, W. R., Jr. (1986). The person-situation debate: A critical multiplist perspective.Journal of Personality 5452–105

    Article  Google Scholar 

  • Huba, G. J., & Harlow, L. L. (1986). Robust estimation for causal models: A comparison of methods in some developmental datasets. In P. B. Baltes, D. M. Featherman, & R. M. Lerner (Eds.)Life-span developmental psychology Vol. 6(pp. 69–111). Hillsdale, NJ: Erlbaum

    Google Scholar 

  • Humphreys, L. G. (1990). View of a supportive empiricist.Psychological Inquiry 1153–155

    Article  Google Scholar 

  • Jareskog, K. G.&Sarbom, D. (1988).LISREL 7: A guide to the program and applicationsChicago: SPSS

    Google Scholar 

  • Judd, C. M.&Kenny, D. A. (1981).Estimating the effects of social interventionsCambridge, MA: Cambridge University Press

    Google Scholar 

  • Kaplan, D. (1988). The impact of specification error on the estimation, testing, and improvement of structural equation models.Multivariate Behavioral Research 2369–86

    Article  Google Scholar 

  • Kellam, S. (1990). Developmental epidemiological framework for family research on depression and aggression. In G. R. Patterson (Ed.)Depression and aggression in family interaction(pp. 11–48). Hillsdale, NJ: Erlbaum

    Google Scholar 

  • Kenny, D. A., & Campbell, D. T. (1989). On the measurement of stability in over-time data.Journal of Personality 57445–481

    Article  PubMed  Google Scholar 

  • Knowles, E. S. (1988). Item context effects on personality scales: Measuring changes the measure.Journal of Personality and Social Psychology 55312–320

    Article  Google Scholar 

  • Kvalseth, T. O. (1985). Cautionary note about R2.The American Statistician 39279–285

    Google Scholar 

  • Labouvie, E. W. (1981). The study of multivariate change structures: A conceptual perspective.Multivariate Behavioral Research 1623–35

    Article  Google Scholar 

  • LaDu, T. J., & Tanaka, J. S. (1995). Incremental fit index changes for nested structural equation models.Multivariate Behavioral Research 30289–316

    Article  Google Scholar 

  • Lazarus, R. S., & DeLongis, A. (1983). Psychological stress and coping in aging.American Psychologist 38245–254

    Article  PubMed  Google Scholar 

  • Loehlin, J. C. (1987).Latent variable models: An introduction to factor path and structural analysisHillsdale, NJ: Erlbaum

    Google Scholar 

  • Loevinger, J. (1957). Objective tests as instruments of psychological theory.Psychological Reports 3635–694

    Google Scholar 

  • Lohmöller, J.-B. (1989).Latent variable path modeling with partial least squaresHeidelberg: Physica-Verlag

    Google Scholar 

  • Lord, F. M. (1958). Further problems in the measurement of growth.Educational and Psychological Measurement 18437–451

    Article  Google Scholar 

  • McArdle, J. J. (1986). Latent variable growth within behavior genetic models.Behavior Genetics 16163–200

    Article  PubMed  Google Scholar 

  • McArdle, J. J. (1988). Dynamic but structural equation modeling of repeated measures data. In J. R. Nesselroade & R. B. Cattell (Eds.)Handbook of multivariate experimental psychology(2nd ed., pp. 561–614). New York: Plenum

    Chapter  Google Scholar 

  • McArdle, J. J., & Epstein, D. (1987). Latent growth curves within developmental structural equation models.Child Development 58110–133

    Article  PubMed  Google Scholar 

  • MacCallum, R. (1986). Specification searches in covariance structure modeling.Psychological Bulletin 100107–120

    Article  Google Scholar 

  • MacCallum, R. (1995). Model specification: Procedures, strategies, and related issues. In R. H. Hoyle (Ed.)Structural evolution modeling(pp. 16–36). Thousand Oaks, CA: Sage

    Google Scholar 

  • Magidson, J. (1977). Toward a causal model approach for adjusting for preexisting differences in the nonequivalent control group situation: A general alternative to ANCOVA.Evaluation Quarterly 1399–420

    Article  Google Scholar 

  • Meehl, P. E. (1990). Appraising and amending theories: The strategy of Lakatosian defense and two principles that warrant using it.Psychological Inquiry 1108–141

    Article  Google Scholar 

  • Meredith, W. (1964a). Notes on factorial invariance.Psychometrika 29177–185

    Article  Google Scholar 

  • Meredith, W. (1964b). Rotation to achieve factorial invariance.Psychometrika29, 187–206

    Article  Google Scholar 

  • Millsap, R. E., & Hartog, S. B. (1988). Alpha, beta, and gamma change in evaluation research: A structural equation approach.Journal of Applied Psychology 73574–584

    Article  Google Scholar 

  • Muthén, B. O. (1987).LISCOMP manualMooresville, IN: Scientific Software

    Google Scholar 

  • Muthén, B. O. (1989). Tobit factor analysis.British Journal of Mathematical and Statistical Psychology 42241–250. Nesselroade, J. R. (1990). Adult personality development: Issues in assessing constancy and change. In A. I. Rabin & R. H. Zucker (Eds.)Studying persons and livesNew York: Springer

    Google Scholar 

  • Nesselroade, J. R. (1988). Some implications of the trait-state distinction for the study of development over the life span: The case of personality. In P. B. Baltes, D. L. Featherman, & R. M. Lerner (Eds.)Life-span development and behavior Vol. 8(pp. 163–189). Hillsdale, NJ: Erlbaum

    Google Scholar 

  • Nesselroade, J. R., & Baltes, P. B. (Eds.). (1979).Longitudinal research in the study of behavior and developmentNew York: Academic

    Google Scholar 

  • Nesselroade, J. R., & Ford, D. H. (1985). P-technique comes of age: Multivariate, replicated, single-subject designs for research on older adults.Research on Aging7, 46–80

    Article  PubMed  Google Scholar 

  • Nunnally, J. C. (1975). The study of change in evaluation research: Principles concerning measurement, experimental design, and analysis. In E. L. Struening & M. Guttentag (Eds.)Handbook of evaluation research Vol. 1(pp. 101–137). Beverly Hills, CA: Sage

    Google Scholar 

  • Panter, A. T., Tanaka, J. S., & Wellens, T. R. (1992). The psychometrics of item order effects. In N. Schwarz & S. Sudman (Eds.)Context effects in survey and psychological testing(pp. 41–85). New York: Springer-Verlag

    Google Scholar 

  • Patterson, G. R., & Bank, L. (1986). Bootstrapping your way in the nomological thicket.Behavioral Assessment 849–73

    Google Scholar 

  • Rogosa, D. (1988). Myths about longitudinal research. In W. Schafe & R. T. Campbell (Eds.)Methodological issues in aging research(pp. 171–209). New York: Springer

    Google Scholar 

  • Rogosa, D. (1979). Causal models in longitudinal research: Rationale, formulation, and interpretation. In J. R. Nesselroade & P. B. Baltes (Eds.)Longitudinal research in the study of behavior and development(pp. 263302). New York: Academic

    Google Scholar 

  • Rogosa, D. (1980). A critique of cross-lagged correlation.Psychological Bulletin 88245–258

    Article  Google Scholar 

  • Rogosa, D., Brandt, D.& ZimowskiM. (1982). A growth curve approach to the measurement of change.Psychological Bulletin 92726–748

    Article  Google Scholar 

  • Rogosa, D., & Ghandour, G. (1991). Statistical models for behavioral observations.Journal of Educational Statistics 16157–252

    Article  Google Scholar 

  • Rogosa, D.&Willett, J. B. (1985a). Satisfying a simplex structure is simpler than it should be.Journal of Educational Statistics 1099–107

    Article  Google Scholar 

  • Rogosa, D. R.&Willett, J. B. (1985b). Understanding correlates of change by modeling individual differences in growth.Psychometrika 50203–228

    Article  Google Scholar 

  • Schmitt, N. (1982). The use of analysis of covariance structures to assess beta and gamma change.Multivariate Behavioral Research 17343–358

    Article  Google Scholar 

  • Seidman, E. (1988). Back to the future, community psychology: Unfolding a theory of social intervention.American Journal of Community Psychology 163–24

    Article  PubMed  Google Scholar 

  • Singer, J. D., & Willett, J. B. (1991). Modeling the days of our lives: Using survival analysis when designing and analyzing longitudinal studies of duration and the timing of events.Psychological Bulletin 110268–298

    Article  Google Scholar 

  • Tanaka, J. S. (1982). The evaluation and selection of adequate causal models: A compensatory education example.Evaluation and Program Planning 511–20

    Article  PubMed  Google Scholar 

  • Tanaka, J. S. (1987). “How big is big enough?”: Sample size and goodness of fit in structural equation models with latent variables.Child Development 58134–146

    Article  Google Scholar 

  • Tanaka, J. S. (1993). Multifaceted conceptions of fit in covariance structure models. In K. A. Bollen & J. S. Long (Eds.)Testing structural equation models(pp. 10–39). Newbury Park, CA: Sage

    Google Scholar 

  • Tanaka, J. S., & Bentler, P. M. (1983). Factor invariance of premorbid social competence across multiple populations of schizophrenics.Multivariate Behavioral Research 18135–146

    Article  Google Scholar 

  • Tanaka, J. S., & Huba, G. J. (1985). A fit index for covariance structure models under arbitrary GLS estimation.British Journal of Mathematical and Statistical Psychology 38197–201

    Article  Google Scholar 

  • Tanaka, J. S., & Huba, G. J. (1987). Assessing the stability of depression in college students.Multivariate Behavioral Research 225–19

    Article  Google Scholar 

  • Tanaka, J. S., & Huba, G. J. (1989). A general coefficient of determination for covariance structure models under arbitrary GLS estimation.British Journal of Mathematical and Statistical Psychology 42233–239

    Article  Google Scholar 

  • Tanaka, J. S., Panter, A. T.&Winborne, W. C. (1988). Dimensions of the need for cognition: Subscales and gender differences.Multivariate Behavioral Research 23 35–50

    Article  Google Scholar 

  • Tanaka, J. S., Panter, A. T., Winborne, W. C., & Huba, G. J. (1990). Theory testing in personality and social psychology with latent variable models: A primer in twenty questions.Review of Personality and Social Psychology 11217–242

    Google Scholar 

  • von Eye, A. (Ed.). (1990).Statistical methods in longitudinal researchVols. 1 & 2. New York: Academic

    Google Scholar 

  • West, S. G., & Hepworth, J. T. (1991). Statistical issues in the study of temporal data: Daily experiences.Journal of Personality 59609–662

    Article  PubMed  Google Scholar 

  • Willett, J. B. (1988). Questions and answers in the measurement of change.Review of Research in Education 15345–422

    Google Scholar 

  • Willett, J. B., Ayoub, C. C.&Robinson, D. (1991). Using growth modeling to examine systematic differences in growth: An example of change in the functioning of families at risk of maladaptive parenting, child abuse, or neglect.Journal of Consulting and Clinical Psychology 3938–47

    Article  Google Scholar 

  • Willett, J. B., & Singer, J. D. (1991). From whether to when: New methods for studying student dropout and teacher attrition.Review of Educational Research 61407–450

    Google Scholar 

  • Zeger, S. L., Liang, K.-Y., & Albert, P. S. (1988). Models for longitudinal data: A generalized estimating equation approach.Biometrics 441049–1060

    Article  PubMed  Google Scholar 

  • Zevon, M. A., & Tellegen, A. (1982). The structure of mood change: An idiographic/nomothetic analysis.Journal of Personality and Social Psychology 43111–122

    Article  Google Scholar 

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  1. Late of the Departments of Educational Psychology and Psychology, University of Illinois at Urbana-Champaign, Champaign, Illinois, 61820, USA

    J. S. Tanaka

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  1. University of Illinois at Urbana-Champaign, Urbana, Illinois, USA

    Julian Rappaport

  2. New York University, New York, New York, USA

    Edward Seidman

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Tanaka, J.S. (2000). Statistical Models for Change. In: Rappaport, J., Seidman, E. (eds) Handbook of Community Psychology. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-4193-6_29

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