Sy-Miin Chow

Sy-Miin Chow
Pennsylvania State University | Penn State · Department of Human Development and Family Studies

Ph.D., Quantitative Psychology

About

104
Publications
19,502
Reads
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2,011
Citations
Citations since 2016
54 Research Items
1382 Citations
2016201720182019202020212022050100150200250
2016201720182019202020212022050100150200250
2016201720182019202020212022050100150200250
2016201720182019202020212022050100150200250
Additional affiliations
July 2007 - July 2012
University of North Carolina at Chapel Hill
Position
  • Professor (Assistant)

Publications

Publications (104)
Article
Full-text available
The ILHBN is funded by the National Institutes of Health to collaboratively study the interactive dynamics of behavior, health, and the environment using Intensive Longitudinal Data (ILD) to (a) understand and intervene on behavior and health and (b) develop new analytic methods to innovate behavioral theories and interventions. The heterogenous st...
Article
Education can be viewed as a control theory problem in which students seek ongoing exogenous input-either through traditional classroom teaching or other alternative training resources-to minimize the discrepancies between their actual and target (reference) performance levels. Using illustrative data from [Formula: see text] Dutch elementary schoo...
Article
In this paper, we present and evaluate a novel Bayesian regime-switching zero-inflated multilevel Poisson (RS-ZIMLP) regression model for forecasting alcohol use dynamics. The model partitions individuals' data into two phases, known as regimes, with: (1) a zero-inflation regime that is used to accommodate high instances of zeros (non-drinking) and...
Article
Full-text available
Global Positioning System (GPS) data have become one of the routine data streams collected by wearable devices, cell phones, and social media platforms in this digital age. Such data provide research opportunities in that they may provide contextual information to elucidate where, when, and why individuals engage in and sustain particular behaviora...
Article
Full-text available
The intelligent tutoring system of structure strategy (ITSS) is a web-based digital tutoring system proven to be effective in helping students recognize and use text structures to comprehend and recall texts. However, little is known about the dynamic learning processes within the ITSS. This study aims to investigate the effects of feedback dosage...
Article
The influx of intensive longitudinal data creates a pressing need for complex modeling tools that help enrich our understanding of how individuals change over time. Multilevel vector autoregressive (mlVAR) models allow for simultaneous evaluations of reciprocal linkages between dynamic processes and individual differences, and have gained increased...
Article
Relationship difficulties are common during the transition to parenthood and may persist for years. Strategies that enhance couples' daily relational experiences early in the parenting years may serve a protective role. In general, engaging in a capitalization attempt (i.e., sharing personal good news) with one's romantic partner and perceiving the...
Article
The use of dynamic network models has grown in recent years. These models allow researchers to capture both lagged and contemporaneous effects in longitudinal data typically as variations, reformulations, or extensions of the standard vector autoregressive (VAR) models. To date, many of these dynamic networks have not been explicitly compared to on...
Article
Researchers collecting intensive longitudinal data (ILD) are increasingly looking to model psychological processes, such as emotional dynamics, that organize and adapt across time in complex and meaningful ways. This is also the case for researchers looking to characterize the impact of an intervention on individual behavior. To be useful, statisti...
Article
This study examined two possible mechanisms, evocative gene–environment correlation and prenatal factors, in accounting for child effects on parental negativity. Participants included 561 children adopted at birth, and their adoptive parents and birth parents within a prospective longitudinal adoption study. Findings indicated child effects on pare...
Article
Full-text available
Objective One of the promises of the experience sampling methodology (ESM) is that a statistical analysis of an individual's emotions, cognitions and behaviors in everyday-life could be used to identify relevant treatment targets. A requisite for clinical implementation is that outcomes of such person-specific time-series analyses are not wholly co...
Preprint
Researchers collecting intensive longitudinal data (ILD) are increasingly looking to model psychological processes, such as emotional dynamics, that organize and adapt across time in complex and meaningful ways. This is also the case for researchers looking to characterize the impact of an intervention on individual behavior. To be useful, statisti...
Article
Head movement is an important but often overlooked component of emotion and social interaction. Examination of regularity and differences in head movements of infant-mother dyads over time and across dyads can shed light on whether and how mothers and infants alter their dynamics over the course of an interaction to adapt to each others. One way to...
Article
Full-text available
Background Spouses often attempt to influence patients' diabetes self-care. Spousal influence has been linked to beneficial health outcomes in some studies, but to negative outcomes in others. Purpose We aimed to clarify the conditions under which spousal influence impedes glycemic control in patients with type 2 diabetes. Spousal influence was hy...
Article
Children should become more effective at regulating emotion as they age. Longitudinal evidence of such change, however, is scarce. This study uses a multiple-time scale approach to test the hypothesis that the self-regulation of emotion—the engagement of executive processes to influence the dynamics of prepotent emotional responses—becomes more eff...
Conference Paper
Research suggests that social relationships have substantial impacts on individuals' health outcomes. Network intervention, through careful planning, can assist a network of users to build healthy relationships. However, most previous work is not designed to assist such planning by carefully examining and improving multiple network characteristics....
Preprint
Research suggests that social relationships have substantial impacts on individuals' health outcomes. Network intervention, through careful planning, can assist a network of users to build healthy relationships. However, most previous work is not designed to assist such planning by carefully examining and improving multiple network characteristics....
Data
Supplemental materials for "Practical Tools and Guidelines for Exploring and Fitting Linear and Nonlinear Dynamical Systems Models." Link provided by publisher in the published article is not working but here are the materials.
Article
Full-text available
Intensive longitudinal data in the behavioral sciences are often noisy, multivariate in nature , and may involve multiple units undergoing regime switches by showing discontinuities interspersed with continuous dynamics. Despite increasing interest in using linear and nonlinear differential/difference equation models with regime switches, there has...
Article
Full-text available
Intensive longitudinal designs involving repeated assessments of constructs often face the problems of nonignorable attrition and selected omission of responses on particular occasions. However, time series models, such as vector autoregressive (VAR) models, are often fit to these data without consideration of nonignorable missingness. We introduce...
Article
Outliers can be more problematic in longitudinal data than in independent observations due to the correlated nature of such data. It is common practice to discard outliers as they are typically regarded as a nuisance or an aberration in the data. However, outliers can also convey meaningful information concerning potential model misspecification, a...
Article
Full-text available
A dynamical system is a system of variables that show some regularity in how they evolve over time. Change concepts described in most dynamical systems models are by no means novel to social and behavioral scientists, but most applications of dynamic modeling techniques in these disciplines are grounded on a narrow subset of—typically linear—theori...
Preprint
Full-text available
One of the promises of the experience sampling methodology (ESM) is that it could be used to identify relevant targets for treatment, based on a statistical analysis of an individual's emotions, cognitions and behaviors in everyday-life. A requisite for clinical implementation is that outcomes of person-centered analyses are not wholly contingent o...
Article
Full-text available
In the study of human dynamics, the behavior under study is often operationalized by tallying the frequencies and intensities of a collection of lower-order processes. For instance, the higher-order construct of negative affect may be indicated by the occurrence of crying, frowning, and other verbal and nonverbal expressions of distress, fear, ange...
Article
Full-text available
With the recent growth in intensive longitudinal designs and the corresponding demand for methods to analyze such data, there has never been a more pressing need for user-friendly analytic tools that can identify and estimate optimal time lags in intensive longitudinal data. The available standard exploratory methods to identify optimal time lags w...
Article
Full-text available
Assessing several individuals intensively over time yields intensive longitudinal data (ILD). Even though ILD provide rich information, they also bring other data analytic challenges. One of these is the increased occurrence of missingness with increased study length, possibly under non-ignorable missingness scenarios. Multiple imputation (MI) hand...
Article
Full-text available
With the recent growth in intensive longitudinal designs and corresponding demand for methods to analyze such data, there has never been a more pressing need for user-friendly analytic tools that can identify and estimate optimal time lags in intensive longitudinal data. Available standard exploratory methods to identify optimal time lags within un...
Article
Objectives. This article models the chain of risk that links life course socioeconomic status (SES), daily stressor exposure and severity, and daily well-being. Method. Data from the main survey and the daily diary project of the Midlife in the United States (MIDUS) Refresher study were combined, resulting in 782 participants (55.6% female; age 25...
Article
Full-text available
A growing number of social scientists have turned to differential equations as a tool for capturing the dynamic interdependence among a system of variables. Current tools for fitting differential equation models do not provide a straightforward mechanism for diagnosing evidence for qualitative shifts in dynamics, nor do they provide ways of identif...
Article
Myriad approaches for handling missing data exist in the literature. However, few studies have investigated the tenability and utility of these approaches when used with intensive longitudinal data. In this study, we compare and illustrate two multiple imputation (MI) approaches for coping with missingness in fitting multivariate time-series models...
Chapter
Self-organization occurs when a system shows distinct shifts in dynamics due to variations in the parameters that govern the system. Relatedly, many human dynamic processes with self-organizing features comprise subprocesses that unfold across multiple time scales. Incorporating time-varying parameters (TVPs) into a dynamic model of choice provides...
Article
Full-text available
This editorial accompanies the second special issue on Bayesian data analysis published in this journal. The emphases of this issue are on Bayesian estimation and modeling. In this editorial, we outline the basics of current Bayesian estimation techniques and some notable developments in the statistical literature, as well as adaptations and extens...
Article
Full-text available
Self-regulation is a dynamic process wherein executive processes (EP) delay, minimize or desist prepotent responses (PR) that arise in situations that threaten well-being. It is generally assumed that, over the course of early childhood, children expand and more effectively deploy their repertoire of EP-related strategies to regulate PR. However, l...
Article
Full-text available
Many psychological concepts are unobserved and usually represented as latent factors apprehended through multiple observed indicators. When multiple-subject multivariate time series data are available, dynamic factor analysis models with random effects offer one way of modeling patterns of within- and between-person variations by combining factor a...
Article
Longitudinal social network analyses were conducted to examine social support exchange among patients with irritable bowel syndrome (IBS) on an online health forum. The analyses of 90,965 messages posted by 9,369 patients from 2008 to 2012 suggest that both receiving and offering support significantly encourage continuous social support exchange. P...
Article
This study explored the use of dynamical systems modeling techniques to evaluate self- and co-regulation of affect in couples' interactions before and after the transition to parenthood, and the impact of the Family Foundations program on these processes. Thirty-four heterosexual couples, randomized to intervention and control conditions, participa...
Article
In the past 20 years, there has been a steadily increasing attention and demand for Bayesian data analysis across multiple scientific disciplines, including psychology. Bayesian methods and the related Markov chain Monte Carlo sampling techniques offered renewed ways of handling old and challenging new problems that may be difficult or impossible t...
Article
Full-text available
We compare the performances of well-known frequentist model fit indices (MFIs) and several Bayesian model selection criteria (MCC) as tools for cross-loading selection in factor analysis under low to moderate sample sizes, cross-loading sizes, and possible violations of distributional assumptions. The Bayesian criteria considered include the Bayes...
Chapter
Full-text available
Dynamic systems modeling techniques provide a convenient platform for representing multidimensional and multidirectional change processes over time. Central to dynamic systems models is the notion that a system may show emergent properties that allow the system to self-organize into qualitatively distinct states through temporal fluctuations in sel...
Article
Objectives: Life-span theories of aging suggest improvements and decrements in individuals' ability to regulate affect. Dynamic process models, with intensive longitudinal data, provide new opportunities to articulate specific theories about individual differences in intraindividual dynamics. This paper illustrates a method for operationalizing af...
Article
We tested the hypothesis that indices of chronic self-regulatory stress specified by Social Action Theory (SAT; Ewart, 2011) and indices of affect specified by the Dynamic Model of Relapse (DMR; Witkiewitz & Marlatt, 2004) predict daily alcohol use by persons in outpatient treatment for alcohol use disorder (AUD). Participants (69 men, 50 women; ag...
Article
Self-regulation can be conceptualized in terms of dynamic tension between highly probable reactions (prepotent responses) and use of strategies that can modulate those reactions (executive processes). This study investigated the value of a dynamical systems approach to the study of early childhood self-regulation. Specifically, ordinary differentia...
Article
The autoregressive latent trajectory (ALT) model synthesizes the autoregressive model and the latent growth curve model. The ALT model is flexible enough to produce a variety of discrepant model-implied change trajectories. While some researchers consider this a virtue, others have cautioned that this may confound interpretations of the model's par...
Article
The present study examined observations of parenting quality (mothers' emotional availability - EA) during infant bedtimes at 4 points across the infants' first year, assessing relations between levels and trajectories of EA and infant attachment at 12 months and the role of infant temperament in moderating these associations. The sample (N = 128)...
Article
Full-text available
Factor analysis is a popular statistical technique for multivariate data analysis. Developments in the structural equation modeling framework have enabled the use of hybrid confirmatory/exploratory approaches in which factor-loading structures can be explored relatively flexibly within a confirmatory factor analysis (CFA) framework. Recently, Muthé...
Article
Measurement burst designs, wherein individuals are measured intensively during multiple periods (i.e., bursts), have created new opportunities for studying change at multiple time scales. This article develops a model that might be useful in situations where the functional form of short-term change is unknown, might consist of multiple phases, and...
Article
Several approaches exist for estimating the derivatives of observed data for model exploration purposes, including functional data analysis (FDA; Ramsay & Silverman, 2005 ), generalized local linear approximation (GLLA; Boker, Deboeck, Edler, & Peel, 2010 ), and generalized orthogonal local derivative approximation (GOLD; Deboeck, 2010 ). These der...
Article
Full-text available
Ambulatory cardiovascular (CV) measurements provide valuable insights into individuals' health conditions in ``real-life,'' everyday settings. Current methods of modeling ambulatory CV data do not consider the dynamic characteristics of the full data set and their relationships with covariates such as caffeine use and stress. We propose a stochasti...
Article
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Catastrophe theory (Thom, 1972, 1993) is the study of the many ways in which continuous changes in a system's parameters can result in discontinuous changes in 1 or several outcome variables of interest. Catastrophe theory-inspired models have been used to represent a variety of change phenomena in the realm of social and behavioral sciences. Despi...
Article
Full-text available
The past decade has evidenced the increased prevalence of irregularly spaced longitudinal data in social sciences. Clearly lacking, however, are modeling tools that allow researchers to fit dynamic models to irregularly spaced data, particularly data that show nonlinearity and heterogeneity in dynamical structures. We consider the issue of fitting...
Chapter
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State–space modeling techniques provide a convenient modeling platform for representing systematic trends as well as patterns of intraindividual variability around these trends. Their flexibility in accommodating multivariate processes renders them particularly suited to studying dyadic and family processes that show complex ebbs and flows over tim...
Article
Full-text available
Multi-trait multi-method (MTMM) models provide a way to assess convergent and discriminant validity when multiple traits are measured by multiple methods. In recent years, longitudinal extensions of MTMM models have been proposed in the structural equation modeling framework to evaluate whether and how the trait as well as method factors change ove...
Article
Full-text available
Exploratory process factor analysis (EPFA) is a data-driven latent variable model for multivariate time series. This article presents analytic standard errors for EPFA. Unlike standard errors for exploratory factor analysis with independent data, the analytic standard errors for EPFA take into account the time dependency in time series data. In add...
Article
Full-text available
Nonlinear dynamic factor analysis models extend standard linear dynamic factor analysis models by allowing time series processes to be nonlinear at the latent level (e.g., involving interaction between two latent processes). In practice, it is often of interest to identify the phases-namely, latent "regimes" or classes-during which a system is char...
Article
Full-text available
Mixture structural equation model with regime switching (MSEM-RS) provides one possible way of representing over-time heterogeneities in dynamic processes by allowing a system to manifest qualitatively or quantitatively distinct change processes conditional on the latent regime the system is in at a particular time point. Unlike standard mixture st...
Article
Full-text available
Mixture structural equation model with regime switching (MSEM-RS) provides one possible way of representing over-time heterogeneities in dynamic processes by allowing a system to manifest qualitatively or quantitatively distinct change processes conditional on the latent “regime” the system is in at a particular time point. Unlike standard mixture...
Article
This paper proposes a generalized random coefficient structural equation model for analyzing longitudinal data by incorporating the correlated structure due to adjacent time effects and by allowing structural parameters to vary across individuals. The coregionalization for modeling multivariate spatial data is adopted to formulate the correlated st...
Article
There has been great interest in developing nonlinear structural equation models and associated statistical inference procedures, including estimation and model selection methods. In this paper a general semiparametric structural equation model (SSEM) is developed in which the structural equation is composed of nonparametric functions of exogenous...