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Representative Publications By Project Members


Chow, S M., Ferrer, E., & Nesselroade, J.R. (2007). An unscented Kalman filter approach to the estimation of nonlinear dynamical systems models. Multivariate Behavioral Research, 42, 283-321.


Chow, S.M., Ferrer, E., & Hsieh, F. (Eds.), Statistical methods for modeling human dynamics: An interdisciplinary dialogue. Notre Dame Series on Quantitative Methodology (Vol. 4). Mahwah, NJ: Lawrence Erlbaum Associates.


Felmlee, D. (2001). No couple is an island: A social network perspective on dyadic stability. Social Forces, 79, 1259-1287.


Felmlee, D. H. (2004). Application of dynamic systems analysis to dyadic interactions In A.D. Ong & M. van Dulmen (Eds.), Handbook of Methods in Positive Psychology. Oxford University Press.


Felmlee, D. H., & Greenberg, D.F. (1999).A dynamic systems model of dyadic interaction. Journal of Mathematical Sociology, 23, 155-180.


Felmlee, D., Sprecher, S., & Bassin, E. (1990). The dissolution of intimate relationships: A hazard model. Social Psychology Quarterly, 53, 13-30.


Felmlee, D., & Sprecher, S. (2000). Close relationships and social psychology: Intersection and future paths. Social Psychology Quarterly, 63, 365-376.


Ferrer, E. (2006). Application of dynamic factor analysis to affective processes in dyads. In A.D. Ong & M. van Dulmen (Eds.), Handbook of Methods in Positive Psychology (pp. 41-58). Oxford University Press.


Ferrer, E. & McArdle, J.J. (2003). Alternative structural models for multivariate longitudinal data analysis. Structural Equation Modeling, 10, 493-524.


Ferrer, E. & Nesselroade, J.R. (2003). Modeling affective processes in dyadic relations via dynamic factor analysis. Emotion, 3, 344-360.


Ferrer, E., Balluerka, N., & Widaman, K.F. (2008). Factorial Invariance and the specification of second-order latent growth models. Methodology, 4, 22-36.


Ferrer, E., Steele, J., Hsieh, F. (2008). Analyzing dynamics of affective dyadic interactions using patterns of intra- and inter-individual variability. Under Review.


Ferrer, E., & Widaman, K. F. (2008). Dynamic factor analysis of dyadic affective processes with inter-group differences. In N.A. Card, J.P. Selig., & T.D. Little (Eds.), Modeling dyadic and interdependent data in the developmental and behavioral sciences (pp. 107-137). Hillsdale, NJ: Psychology Press.


Ferrer, E., & Zhang, G. (in press). Time series models for examining psychological processes: Applications and new developments. In R. E. Millsap, & A. Madeu-Olivares (Eds.), Handbook of quantitative methods in psychology. Sage.


Hsieh, F., Ferrer, E., Chen, S., Mauss, I.B., & Gross, J.L. (2008). A small-world network approach for evaluating coherence in multivariate systems: An application to psycho-physiological emotion data. Under Review.


Hsieh, F., Ferrer, E., Chen, S., & Chow, S.-M. (2008). Exploring nonstationary dynamics in dyadic interactions via hierarchical segmentation and stochastic small-world networks. Under Review.


Hsieh, F., Chen, S., Chow, S.M., & Ferrer, E. (in press). Exploring intra-individual, inter-individual and inter-variable dynamics in dyadic interactions. In S.M. Chow, E. Ferrer, & F. Hsieh (Eds.), Statistical methods for modeling human dynamics: An interdisciplinary dialogue. Notre Dame Series on Quantitative Methodology (Vol. 4). New York, NY: Taylor and Francis.


Hsieh, F., McAssey, M., & Ferrer, E. (2009). Optimal and robust design for efficient system-wide synchronization in networks of randomly-wired neuron-nodes. Under Review.


Reise, S. P., & Widaman, K. F.  (1999). Assessing the fit of measurement models at the individual level: A comparison of item response theory and covariance structure approaches.  Psychological Methods, 4, 3-21.


Sbarra, D.A., & Ferrer, E. (2006). The Structure and process of emotional experience following non-marital relationship dissolution: Dynamic factor analyses of love, anger, and sadness. Emotion, 6, 224-238.


Sbarra, D.A., Ferrer, E., & Hazan, C. (2004). Changes in heart rate operate as a function of normative adult attachment: Evidence from a laboratory gazing task. Paper presented at the Society for Psychophysiological Research (SPR) Conference, Santa Fe, NM.


Song, H., & Ferrer, E. (in press). State-space modeling of dynamic psychological processes via the Kalman smoother algorithm: Rationale, finite sample properties, and applications. Structural Equation Modeling.


Widaman, K. F.  (2000). Testing cross-group and cross-time constraints on parameters using the general linear model.  In T. D. Little, K. U. Schnabel, & J. Baumert (Eds.), Modeling longitudinal and multilevel data: Practical issues, applied approaches, and specific examples (pp. 163-185).  Mahwah, NJ: Erlbaum.


Widaman, K. F., & Thompson, J. S. (2003). On specifying the null model for incremental fit indices in structural equation modeling. Psychological Methods, 8, 16-37.




2009.  University of California, Davis -- Department of Psychology
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