Whats for dynr: A Package for Linear and Nonlinear Dynamic Modeling in R

Ou, Lu; Hunter, Michael D.; Chow, Sy Miin

doi:10.32614/rj-2019-012

Cited by 44 publications

(42 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Recent advances in continuous time modeling (Driver, Oud, & Voelkle, 2017;Estrada & Ferrer, 2019;Ji & Chow, 2018;Ou, Hunter, & Chow, 2017;Voelkle & Oud, 2015;Voelkle, Oud, Davidov, & Schmidt, 2012) allow a wide variety of possibilities for the study of dynamic systems. Applying these analytic frameworks could provide rich information about how the lead-lag effects between brain structure and cognitive ability Time-lagged associations between cognitive and cortical development -29 change as a function of the time lag.…”

Section: Limitations and Future Directionsmentioning

confidence: 99%

Time-lagged associations between cognitive and cortical development from childhood to early adulthood.

Estrada¹,

Ferrer²,

Román³

et al. 2019

Developmental Psychology

View full text Add to dashboard Cite

Throughout childhood and adolescence, humans experience marked changes in cortical structure and cognitive ability. Cortical thickness and surface area, in particular, have been associated with cognitive ability. Here we ask the question: What are the timerelated associations between cognitive changes and cortical structure maturation. Identifying a developmental sequence requires multiple measurements of these variables from the same individuals across time. This allows capturing relations among the variables and, thus, finding whether: (a) developmental cognitive changes follow cortical structure maturation, (b) cortical structure maturation follows cognitive changes, or (c) both processes influence each other over time. 430 children and adolescents (age range = 6.01-22.28 years) completed the WASI battery and were MRI scanned at three time points separated by ≈ 2 years (mean age t1 = 10.60, SD = 3.58, mean age t2=12.63, SD=3.62, mean age t3=14.49, SD=3.55). Latent Change Score (LCS) models were applied to quantify age-related relationships among the variables of interest. Our results indicate that cortical and cognitive changes related to each other reciprocally. Specifically, the magnitude or rate of the change in each variable at any occasion-and not the previous levelwas predictive of later changes. These results were replicated for brain regions selected according to the coordinates identified in the Basten et al.'s (2015) meta-analysis, to the Parieto-Frontal Integration Theory (P-FIT, Jung & Haier, 2007) and to the whole cortex. Potential implications regarding brain plasticity and cognitive enhancement are discussed.

show abstract

Section: Limitations and Future Directionsmentioning

confidence: 99%

Time-lagged associations between cognitive and cortical development from childhood to early adulthood.

Estrada¹,

Ferrer²,

Román³

et al. 2019

Developmental Psychology

View full text Add to dashboard Cite

show abstract

“…Last but not least, the statistical model simultaneously represents both between-and within-subject qualitative and quantitative variability that is prevalent in students' learning processes. It extends many traditional models, including finite mixture models [8,9], hidden Markov models [5,20], and regime-switching dynamic models [7,14], to enable crucial inferences of students' learning processes to inform interventions.…”

Section: Introductionmentioning

confidence: 99%

Using a cluster-based regime-switching dynamic model to understand embodied mathematical learning

Ou¹,

Andrade²,

Alberto

et al. 2020

Proceedings of the Tenth International Conference on Learning Analytics &Amp; Knowledge

Self Cite

View full text Add to dashboard Cite

Embodied learning and the design of embodied learning platforms have gained popularity in recent years due to the increasing availability of sensing technologies. In our study, we made use of the Mathematical Imagery Trainer for Proportion (MIT-P) that uses a touchscreen tablet to help students explore the concept of mathematical proportion. The use of sensing technologies provides an unprecedented amount of high-frequency data on students' behaviors. We investigated a statistical model called mixture Regime-Switching Hidden Logistic Transition Process (mixRHLP) and fit it to the students' hand motion data. Simultaneously, the model finds characteristic regimes and assigns students to clusters of regime transitions. To understand the nature of these regimes and clusters, we explore some properties in students' and tutor's verbalization associated with these different phases.

show abstract

“…The development of new estimation packages means that the application of the CT modeling approach has never been easier (Boker et al, 2004;Boker, Deboeck, et al, 2010;Ou et al, 2017). The call for a more widespread adoption of CT models is matched by a growing number of applications of these models in substantive areas (e.g., Toharudin et al, 2008;Boker, Montpetit, et al, 2010;Steele & Ferrer, 2011;Angraini et al, 2014;Chow et al, 2018).…”

Section: Discussionmentioning

confidence: 99%

Interventions in dynamic systems: A causal approach to continuous-time mediation analysis

Ryan¹

2018

Preprint

View full text Add to dashboard Cite

Mediation analysis plays a central role in the investigation of causal mechanisms, where the total, direct and indirect influence of one variable on another is typically assessed using path-tracing rule}. Two recent developments promise to revolutionize mediation analysis: first, the interventionist causal inference framework has allowed researchers to define and investigate mediation in terms of interventions on variables rather than path-tracing rules; second, researchers have begun to use Continuous-Time (CT) models to investigate mediation in longitudinal data. This paper shows how CT mediation can be treated using an interventionist approach. The links between interventionist and path-tracing definitions in traditional longitudinal SEM models and in CT models are explored in detail. The treatment of mediation from diverse strands of literature is unified, by showing how total, direct and indirect effects in different frameworks can be defined as qualitatively different types of interventions on the values of variables.

show abstract

Whats for dynr: A Package for Linear and Nonlinear Dynamic Modeling in R

Cited by 44 publications

References 46 publications

Time-lagged associations between cognitive and cortical development from childhood to early adulthood.

Time-lagged associations between cognitive and cortical development from childhood to early adulthood.

Using a cluster-based regime-switching dynamic model to understand embodied mathematical learning

Interventions in dynamic systems: A causal approach to continuous-time mediation analysis

Contact Info

Product

Resources

About