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Todd D. Little

Director, Quantitative Program
Director, Center for Research Methods and Data Analysis

Ph.D., 1988, University of California at Riverside
Research Areas: Quantitative Psychology, Developmental Psychology

Related Links
Quantitative Psychology Program
Developmental Psychology Program
Lab Page
Center for Research Methods and Data Analysis
Summer Institute

Research Interests

Using a unifying theoretical perspective, I study developmental changes in how children's and adolescents' action-control processes (i.e., motivational and self-regulation) influence (a) their adjustment and achievement in school settings, (b) their peer and friendship relationships, (c) their reasons for aggression and victimization, and (d) their ability to cope with challenging and stressful events. I examine these topics with a special focus on cross-cultural and sociocontextual influences (e.g., ethnic differences, socialization processes). In support of my substantive work, I specialize and provide graduate-level training in an array of multivariate statistical techniques including structural equation modeling (e.g., LISREL), growth curve modeling, and the like. In this regard, I also do work examining the use of structural equation modeling techniques as a general data analytic approach to studying individual, developmental, and sociocontextual differences. My research foci share a number of commonalities. For example, they share an emphasis on the self-regulatory processes of individuals, the meta-theoretical cohesion of action-control theory, and the methodological consistency of using the most appropriate individual- and group-differences analytic system available. Because I examine self-regulatory processes developmentally and within situated (e.g., cross-cultural) contexts, my research covers topics of central relevance to cross-cultural, developmental, social, personality, and educational psychology.

Selected Publications

Developmental Research

  • Geldhof, G. J., Little, T.D., & Colombo, J. (in press). Self-regulation across the lifespan. In M. E. Lamb & A. M. Freund (Vol. Eds.), and R. M. Lerner (Editor-in-Chief). Social and emotional development. Volume 2 of The Handbook of Lifespan Development. Hoboken, NJ: Wiley.
  • Card, N. A., & Little, T.D. (2006). Proactive and reactive aggression in childhood and adolescence: A meta-analysis of differential relations with psychosocial adjustment. International Journal of Behavioral Development, 30, 466-480.
  • Vanlede, M., Little, T.D., & Card, N. A. (2006). Action-control beliefs and behaviors as predictors of change in adjustment across the transition to middle school. Anxiety, Stress, and Coping, 19, 111-127.
  • Walls, T. A. & Little, T.D. (2005). Relations among personal agency, motivation, and school adjustment in early adolescence. Journal of Educational Psychology, 97, 23-31.

Quantitative Research

  • Little, T.D., Card, N. A., Preacher, K. J., & McConnell, E. (2009). Modeling longitudinal data from research on adolescence. In R. M. Lerner & L. Steinberg (Eds.), Handbook of adolescent psychology (3rd ed, pp. 15-54.). Hoboken, NJ: Wiley.
  • Little, T.D., Preacher, K. J., Selig, J. P., & Card, N. A. (2007). New developments in SEM panel analyses of longitudinal data. International Journal of Behavioral Development, 31, 357-365.
  • Little, T.D., Bovaird, J. A., & Widaman, K. F. (2006). On the merits of orthogonalizing powered and product terms: Implications for modeling interactions among latent variables. Structural Equation Modeling, 13 ,497-519.
  • Little, T.D., Slegers, D. W., & Card, N. A. (2006). A non-arbitrary method of identifying and scaling latent variables in SEM and MACS models. Structural Equation Modeling, 13, 59-72.

Recent Edited Books

  • Card, N. A., Selig, J. P., & Little, T.D. (Eds.) (2008). Modeling dyadic and interdependent data in developmental research. Mahwah, NJ: LEA.
  • Hawley, P. H., Little, T.D., & Rodkin, P. (Eds.). (2007). Aggression and adaptation. Mahwah, NJ: LEA
  • Little, T.D., Bovaird, J. A., & Card, N. A. (Eds.) (2007). Modeling contextual effects in longitudinal studies. Mahwah, NJ: LEA

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