A Person- and Time-Varying Vector Autoregressive Model to Capture Interactive Infant-Mother Head Movement Dynamics
Datos Bibliográficos
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 study these emergent differences in dynamics is to allow parameters that govern the patterns of interactions to change over time, and according to person- and dyad-specific characteristics. Using two estimation approaches to implement variations of a vector-autoregressive model with time-varying coefficients, we investigated the dynamics of automatically-tracked head movements in mothers and infants during the Face-Face/Still-Face Procedure (SFP) with 24 infant-mother dyads. The first approach requires specification of a confirmatory model for the time-varying parameters as part of a state-space model, whereas the second approach handles the time-varying parameters in a semi-parametric (“mostly” model-free) fashion within a generalized additive modeling framework. Results suggested that infant-mother head movement dynamics varied in time both within and across episodes of the SFP, and varied based on infants’ subsequently-assessed attachment security. Code for implementing the time-varying vector-autoregressive model using two R packages, dynr and mgcv, is provided
Autoregressive model · Biology · Dynamics (music) · Econometrics · Head (geology) · Machine learning · Movement (music) · Statistics · Artificial Intelligence · Computer Science · Infant Health and Development · Mathematics · Neuroendocrine regulation and behavior · Neuroscience of respiration and sleep · Psychology
Fitting the Longitudinal Actor-Partner Interdependence Model as a Dynamic Structural Equation Model in M plus
Dynamics of learning
A Growth of Hierarchical Autoregression Model for Capturing Individual Differences in Changes of Dynamic Characteristics of Psychological Processes
Integrated Trend and Lagged Modeling of Multi-Subject, Multilevel, and Short Time Series
Homogeneity Assumptions in the Analysis of Dynamic Processes
Reject All Splits
Stan
Thin Plate Regression Splines
Information Theory and an Extension of the Maximum Likelihood Principle
Varying-Coefficient Models
The Infant's Response to Entrapment between Contradictory Messages in Face-to-Face Interaction
Fast Stable Restricted Maximum Likelihood and Marginal Likelihood Estimation of Semiparametric Generalized Linear Models
The origins of 12-month attachment
Emotional Inertia and Psychological Maladjustment
Infant Stress and Parent Responsiveness
A New Approach to Linear Filtering and Prediction Problems
Estimating the Dimension of a Model
Dynamic Factor Analysis in the Frequency Domain
At the Frontiers of Modeling Intensive Longitudinal Data
Practical Tools and Guidelines for Exploring and Fitting Linear and Nonlinear Dynamical Systems Models
Modeling Nonstationary Emotion Dynamics in Dyads using a Time-Varying Vector-Autoregressive Model
An Unscented Kalman Filter Approach to the Estimation of Nonlinear Dynamical Systems Models
Dynamic Factor Analysis Models With Time-Varying Parameters
Representing Sudden Shifts in Intensive Dyadic Interaction Data Using Differential Equation Models with Regime Switching
Dynamic infant–parent affect coupling during the face-to-face/still-face
Self-regulation and emotion in infancy
Bodily expression of emotion
Antecedents of self-regulation
Infant response to the still-face situation at 3 and 6 months
Mother-infant face-to-face interaction
Analyzing developmental processes on an individual level using nonstationary time series modeling
A systems view of mother–infant face-to-face communication
Detecting deception from the body or face
Some signals and rules for taking speaking turns in conversations
Coordination
Infant-mother and infant-father synchrony
| Obras citantes distintas | 6 |
|---|---|
| Citas por año | 1,2 |
| Intervalo de citas | 2021 - 2026 (6) |
| Velocidad de citación | current |
| Altamente citado | No |
| Tipos de cita | Neutras: 6 |