PUBLICATIONS 2017-10-24T20:22:25+00:00

Books

Van der Ark, A., Bolt, D.,Wang, W-C., Douglas, J., & Chow, S-M. (Eds), (2015).
Quantitative Psychology Research: Proceedings of the 79th Annual International Meeting of the Psychometric Society. Switzerland: Springer International Publishing.

Chow, S-M., Ferrer, E., & Hsieh, F. (Eds.) (2009). Statistical methods for modeling human dynamics: An interdisciplinary dialogue. Notre Dame Series on Quantitative Methodology (Vol. 4). New York, NY: Taylor & Francis.

Published/In Press

Ou, L., Hunter, M., & Chow, S-M. (under review). What’s for dynr: A package for linear and nonlinear dynamic modeling in R. Journal of Statistical Software.

Yang, F., Zhong, B., Kumar, A., Chow, S-M., & Ouyang, A. (in press).  Motivating Social Support Online: A Big-Data Analysis of IBS Patients’ Interaction on a Health Forum from 2008 to 2012. Journalism and Mass Communication  Quarterly. Special Issue on Advances in Global Health Communication

Chen, M., Chow, S-M., & Hunter, M. (in press). Stochastic differential equation models with time-varying parameters. In K. van Montford,, H. Oud, & M. Voelkle (Eds.). Continuous-Time Modeling in the Behavioral and Related Sciences. Berlin: Springer-Verlag.

Ji, L., & Chow, S-M. (in press). Methodological Issues and Extensions to the Latent Difference Score Framework. In Ferrer, M., Grimm, K., & Boker, S.M. (Eds.). Advances in Longitudinal Models for Multivariate Psychology: A Festschrift for Jack McArdle.

Feinberg, M. E., Xia, M., Fosco, G. M., & Chow, S-M. (in press). Dynamical systems modeling of couple interaction: A new method for assessing intervention impact across the transition to parenthood. Prevention Science.

Chow, S-M. & Hoijtink, H., & (in press). Bayesian estimation and modeling: Editorial to the second special issue on Bayesian data analysis, Psychological Methods.

Chow, S-M. & Hoijtink, H. (Eds., in press). Special issue II on Bayesian data analysis, Psychological Methods.

Hoijtink, H., & Chow, S-M. (in press). Bayesian hypothesis testing: Editorial to the first special issue on Bayesian data analysis, Psychological Methods.

Hoijtink, H., & Chow, S-M. (Eds., in press). Special issue I on Bayesian data analysis, Psychological Methods. Maisto, S. A., Xie, F. C., Witkiewitz, K., Ewart, C. K., Connors, G. J., Zhu, H, Elder, G.,

Ditmar, M., & Chow, S-M. (in press). Prediction of daily alcohol consumption by proximal and distal factors derived from Social Action Theory in men and women in outpatient treatment for alcohol use disorder: A zero-inflated poison mixed model for drinking data with missing responses. Journal of Social and Clinical Psychology.

Wood, J., Oravecz, Z., Vogel, N, Benson, L. Chow, S-M., Cole, P., Conroy, D. E., Pincus, A. L., & Ram, N. (in press). Modeling intraindividual dynamics using stochastic differential equations: An examination of age-related differences in affect regulation. Special Issue on: Methodological Innovations in Gerontology: Advances in Psychosocial Research. The Journal of Gerontology, Series B: Psychological Sciences and Social Sciences.

Lu, Z-H., Chow, S-M., & Loken, E. (in press). A Comparison of Bayesian and Frequentist Model Selection Methods for Factor Analysis Models. Psychological Methods.

Cole, P. M., Bendezú, J. J., Ram, N., & Chow, S-M. (in press). Dynamical Systems Modeling of Early Childhood Self-Regulation. Emotion.

Kim, B-R., Chow, S-M., Bray, B., & Teti, D M. (2017). Trajectories of mothers’ emotional availability: Relations with infant temperament in predicting attachment security. Attachment & Human Development, 19(1), 38-57.

Ou, L., Chow, S-M., Ji, L., & Molenaar, P. C. M. (2017). (Re)evaluating the Implications of the autoregressive latent trajectory model through likelihood ratio tests of its initial conditions. Multivariate Behavioral Research, 52(2), 178-199. http://dx.doi.org/10.1080/00273171.2016.1259980

Chow, S-M., Ou, O. Cohn, J. F., & Messinger D. S. (2017). Representing self-organization and non-stationarities in dyadic interaction processes using dynamic systems modeling techniques. In Von Davier, A. Kyllonen, P. C., & Zhu, M. Innovative Assessment of Collaboration. New York: Springer.

Little, T. D., Roche, K. M., Chow, S-M., Schenck, A. P., & Byam, L. A. (2016). National Institutes of Health Pathways to Prevention Workshop: Advancing Research to Prevent Youth Suicide. Annals of Internal Medicine, 165(11), 795-799.

Lu, Z-H., Chow, S-M., & Loken, E. (2016). Bayesian factor analysis as a variable selection problem. Multivariate Behavioral Research, 51(4), 519-539.

Helm, J. L., Ram, N., Cole, P., Chow, S. M. (2016). Modeling self-regulation as a process using a multiple time scale multiphase latent basis growth model. Structural Equation Modeling, 23(5), 635-648. DOI:10.1080/10705511.2016.1178580

Chow, S-M., Bendezú, J. J., Cole, P. M., & Ram, N. (2016). A Comparison of Two-Stage Approaches for Fitting Nonlinear Ordinary Differential Equation (ODE) Models with Mixed Effects. Multivariate Behavioral Research, 51, 154-184. Doi: 10.1080/00273171.2015.1123138.

Chow, S-M., Lu, Z., Sherwood, A. & Zhu, H. (2016). Fitting nonlinear differential equation models with random effects and unknown initial conditions using the stochastic approximation expectation-maximization (SAEM) algorithm. Psychometrika, 81(1), 102-134. Doi:10.1007/s11336-014-9431-z.  PubMed #: 25416456

Lu, Z-H., Chow, S-M., Sherwood, A, & Zhu, H. (2015). Bayesian analysis of ambulatory cardiovascular dynamics with application to irregularly spaced sparse data. Annals of Applied Statistics, 9(3), 1601-1620. Doi: 10.1214/15-AOAS846.

Chow, S-M., Witkiewitz, K. Grasman, R., & Maisto, S. (2015). The Cusp Catastrophe Model as Cross-Sectional and Longitudinal Mixture Structural Equation Models. Psychological Methods, 20, 142-164. PubMed # 25822209 NIHMSID 667553

Hutton, R. S., & Chow, S-M. (2014). Longitudinal Multi-Trait-State-Method model using ordinal data. Multivariate Behavioral Research, 49, 269-282.

Zhang, G., Browne, W. M., Ong, A. D., & Chow, S.-M. (2014). Analytic standard errors for exploratory process factor analysis. Psychometrika, 79(3), 444-469.

Chow, S-M., Mattson, W. I. & Messinger, D. S. (2014). Representing trends and moment-to-moment variability in dyadic and family processes using state-space modeling techniques. In Booth, A., McHale, S., & Landale, N. (Eds.). Emerging Methods in Family Research, Fourth National Symposium on Family Issues. Switzerland: Springer International Publishing.

Chow, S-M., Witkiewitz, K., Grasman, R., Hutton, R. S. & Maisto, Stephen. (2014). A regime-switching longitudinal model of alcohol lapse-relapse. In P. C. M. Molenaar, K. M. Newell, &  R. M. Lerner, Handbook of Relational Developmental Systems: Emerging Methods and Concepts (pp. 397-422). New York: Guilford Publications, Inc.

Messinger, D. S., Mahoor, M. H., Chow, S.-M., Haltigan, J. D., Vadavid, S., & Cohn, J. (2014). Early emotional communication: Novel approaches to interaction. In J. Gratch and S. Marsella (Eds.), Social Emotions in Nature and Artifact (pp. 162-180). New York, NY: Oxford University Press.

Chow, S-M., Grimm, K. J., Filteau, G., Dolan, C. V, & McArdle, J. J. (2013). Regime-switching bivariate dual change score model. Multivariate Behavioral Research, 48(4), 463-502.

Chow, S-M, & Zhang, G. (2013). Regime-switching nonlinear dynamic factor analysis models. Psychometrika, 78(4), 740-768.

Song, X.-Y., Tang, N.-S., Chow, S-M. (2012). Bayesian approach for generalized random coefficient structural equation models for longitudinal data with adjacent time effects. Computational Statistics and Data Analysis, 56(12), 4190-4203.

Guo, R., Zhu, H., Chow, S-M., & Ibrahim, J. G. (2012). Bayesian Lasso for semiparametric structural equation models. Biometrics, 68, 567-577.

Chow, S-M. Zu, J., Shifren, K. & Zhang, G. (2011). Dynamic factor analysis models with time-varying parameters. Multivariate Behavioral Research, 46(2), 303-339.

Algoe, S. B., Fredrickson, B. L., & Chow, S-M. (2011). The future of emotions research within positive psychology. In K. M. Sheldon, T. B. Kashdan, & M. F. Steger (Eds.) Designing positive psychology: Taking stock and moving forward (pp. 115-132).  New York: Oxford University Press.

Chow, S-M., Tang, N., Yuan, Y., Song, X & Zhu, H. (2011). Bayesian estimation of semiparametric dynamic latent variable models using the Dirichlet process prior.  British Journal of Mathematical and Statistical Psychology, 64(1), 69-106.

Zhang, G., Chow, S-M. & Ong, A. D. (2011). A sandwich-type standard error estimator of SEM models with a single time series. Psychometrika,76 (1), 77-96.

Yang, M-S. & Chow, S-M. (2010). Using state-space models with regime switching to represent the dynamics of facial electromyography (EMG) data. Psychometrika, 74(4), 744-771

Hsieh, F., Ferrer, E., Chen, Shu-Chun & Chow, S-M. (2010). Dynamics of dyadic interactions I: Exploring non-stationarity of intra- and inter-individual affective processes via hierarchical segmentation and stochastic small-world networks. Psychometrika, 75(2), 351-372.

Chow, S-M., Haltigan, J. D. & Messinger, D. S. (2010). Dynamic patterns of infant-parent interactions during Face-to-Face and Still-Face episodes. Emotion, 10(1), 101-114.

Chow, S-M. & Filteau, G. (2010). A State-space approach to representing discontinuous shifts in change processes.  In P. C. M. Molenaar & K. M. Newell

(Eds.) Individual Pathways of Change in Learning and Development (pp. 87-108). Washington, D.C.: American Psychological Association.

Zhang, G. & Chow, S-M. (2010). Standard error estimation in stationary multivariate time series models using residual-based bootstrap procedures. In P. C. M. Molenaar & K. M. Newell (Eds.) Individual Pathways of Change in Learning and Development (pp. 169-182). Washington, D.C.: American Psychological Association.

Schermerhorn, A. C., Chow, S-M, & Cummings, E. M. (2010). Developmental family processes and interparental conflict: Patterns of micro-level influences. Developmental Psychology, 46(4), 869-885.

Chow, S-M., Ho, M. H. R., Hamaker, E. & Dolan, C. (2010). Equivalence and differences between structural equation modeling and state-space modeling techniques. Structural Equation Modeling, 17, 303-332.

Chow, S-M., Hamaker, E. & Allaire, J. C. (2009). Using innovative outliers to detect discrete shifts in dynamics in group-based state-space models. Multivariate Behavioral Research, 44, 465-496.

Ferrer, E., Chen, S-C., Chow, S-M. & Hsieh F. (2009). Exploring intra- and inter individual dynamics in dyadic interactions through hierarchical factor segmentation. In Chow, S-M., Ferrer, E., & Hsieh, F. (Eds.), Statistical methods for modeling human dynamics: An interdisciplinary dialogue (pp. 381–411). New York, NY: Taylor & Francis.

Ong, A. D., Bergeman, C. S., & Chow, S-M. (2009). Positive emotions as a basic building block of resilience in later life. In J. Reich, A. Zautra, and J. Hall (Eds.). Handbook of adult resilience: Concepts, methods, and applications (pp. 81-93). New York: Guildford Press.

Chow, S-M., Hamaker, E., Fujita, F., & Boker, S. M. (2009). Representing time-varying cyclic dynamics using multiple-subject state-space models. British Journal of Mathematical and Statistical Psychology, 62, 683-712.

Messinger, D.S., Mahoor, M. H., Chow, S-M., & Cohn, J. F. (2009). Automated measurement of facial expression in infant-mother interaction: A pilot study. Infancy. 14(3), 285-305.

Messinger DS, Mahoor MH, Cadavid S, Chow SM, Cohn JF. (2008). Early Interactive Emotional Development. IEEE Int Conf Dev Learn, 232-237. PubMed PMID: 21804955; PubMed Central PMCID: PMC3145460.

Chow, S-M. & Zhang, G. (2008). Continuous-time modeling of irregularly spaced panel data using a cubic spline interpolation technique. Special issue on “Continuous-time modeling of panel data” coedited by J. H. L. Oud & H. Singer. Statistica Neerlandica 61(1), 131-154.

Chow, S-M., Grimm, K. J. Fujita, F. & Ram, N (2007). Exploring cyclic change in emotion using item response models and frequency-domain analysis In A. Ong & M. van Dulmen (Eds.), Handbook of Methods in Positive Psychology (pp. 362-379). Oxford University Press.

Chow, S-M (2007). Factor score and parameter estimation in nonlinear dynamical systems models. In K. van Montfort, H. Oud & A. Satorra.(Eds.), European Association of Methodology (EAM) Methodology and Statistics series (2nd Vol.): Longitudinal models in the behavioral and related sciences (pp. 107-138). Lawrence Erlbaum.

Chow, S-M., Hamagami, F & Nesselroade, J. R (2007). Age differences in dynamical emotion-cognition linkages. Psychology and Aging, 22(4), 765-780.

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(2), 283-321.

Chow, S-M. & Tiberio, S. S. (2007). Discussion on Ramsey et al.’s paper, “Parameter estimation for differential equations: A generalized smoothing approach”. Journal of the Royal Statistical Society: Series B.

Ram, N., Chow, S-M., Bowles, R. P., Wang, L., Grimm, K. J., Fujita, F. & Nesselroade, J. R (2005). Examining interindividual differences in cyclicity of pleasant and unpleasant affects using spectral analysis and item response modeling. Psychometrika: Application Reviews and Case Studies, 70, 773-790.

Chow, S-M., Ram, N., Boker, S. M., Fujita, F. Clore, G. (2005). Emotion as a thermostat: Representing emotion regulation using a damped oscillator model. Emotion. 5(2), 208-225.

Chow, S-M., Nesselroade, J. R., Shifren, K. & McArdle J. J. (2004). Dynamic structure of emotions among individuals with Parkinson’s disease. Structural Equation Modeling, 11(4), 560-582.

Chow, S-M. & Nesselroade, J.  R. (2004) General slowing or decreased inhibition? Mathematical models of age differences in cognitive functioning. Journals of Gerontology: Psychological Sciences, 59B(3), 101-109.

Walpole, S., Chow, S-M. & Justice, L. (2004). Literacy achievement during kindergarten: Identifying key contributors in an at-risk sample. Early Education and Child Development, 15(3), 245-264.

Justice, L., Chow, S., Michel, C. & Flanigan, K. (2003). Investigation of two emergent literacy enhancement approaches for vulnerable preschoolers. American Journal of Speech-Language Pathology, 12, 1-14.

Chow, S. & Nesselroade, J. R. (2002). Age differences in transitory cognitive performance. In W. Gray & C. Schunn (Eds.), Proceedings of the Twenty-Fourth Annual Conference of the Cognitive Science Society, 196-201.