A Note on the Usefulness of Constrained Fourth-Order Latent Differential Equation Models in the Case of Small T

Constrained fourth-order latent differential equation (FOLDE) models have been proposed (e.g., Boker et al. 2020) as alternative to second-order latent differential equation (SOLDE) models to estimate second-order linear differential equation systems such as the damped linear oscillator model. When, however, only a relatively small number of measurement occasions T are available (i.e., T=50), the recommendation of which model to use is not clear (Boker et al. 2020). Based on a data set, which consists of T=56 observations of daily stress for N=44 individuals, we illustrate that FOLDE can help to choose an embedding dimension, even in the case of a small T. This is of great importance, as parameter estimates depend on the embedding dimension as well as on the latent differential equations model. Consequently, the wavelength as quantity of potential substantive interest may vary considerably. We extend the modeling approaches used in past research by including multiple subjects, by accounting for individual differences in equilibrium, and by including multiple instead of one single observed indicator.Peer Reviewe

Adaptive equilibrium regulation: A balancing act in two timescales

An equilibrium involves a balancing of forces. Just as one maintains upright posture in standing or walking, many self-regulatory and interpersonal behaviors can be framed as a balancing act between an ever changing environment and within-person processes. The emerging balance between person and environment, the equilibria, are dynamic and adaptive in response to development and learning. A distinction is made between equilibrium achieved solely due to balancing of forces and preferred equilibrium which we define as a state towards which the slowly system adapts. This framework conceives regulation as having two time scales: a fast regulation that automatically balances forces and a slower timescale adaptation process that reconfigures the fast regulation so as to move the system towards preferred equilibrium when an environmental force persists over longer time scales. This way of thinking leads to methods for modeling the interplay between multiple timescales of behavior, learning, and development

Parallel Workflows for Data-Driven Structural Equation Modeling in Functional Neuroimaging

We present a computational framework suitable for a data-driven approach to structural equation modeling (SEM) and describe several workflows for modeling functional magnetic resonance imaging (fMRI) data within this framework. The Computational Neuroscience Applications Research Infrastructure (CNARI) employs a high-level scripting language called Swift, which is capable of spawning hundreds of thousands of simultaneous R processes (R Development Core Team, 2008), consisting of self-contained SEMs, on a high performance computing system (HPC). These self-contained R processing jobs are data objects generated by OpenMx, a plug-in for R, which can generate a single model object containing the matrices and algebraic information necessary to estimate parameters of the model. With such an infrastructure in place a structural modeler may begin to investigate exhaustive searches of the model space. Specific applications of the infrastructure, statistics related to model fit, and limitations are discussed in relation to exhaustive SEM. In particular, we discuss how workflow management techniques can help to solve large computational problems in neuroimaging

Dynamics of Change and Change in Dynamics

A framework is presented for building and testing models of dynamic regulation by categorizing sources of differences between theories of dynamics. A distinction is made between the dynamics of change, i.e., how a system self–regulates on a short time scale, and change in dynamics, i.e., how those dynamics may themselves change over a longer time scale. In order to clarify the categories, models are first built to estimate individual differences in equilibrium value and equilibrium change. Next, models are presented in which there are individual differences in parameters of dynamics such as frequency of fluctuations, damping of fluctuations, and amplitude of fluctuations. Finally, models for within–person change in dynamics over time are proposed. Simulations demonstrating feasibility of these models are presented and OpenMx scripts for fitting these models have been made available in a downloadable archive along with scripts to simulate data so that a researcher may test a selected models’ feasibility within a chosen experimental design

Nonverbal Synchrony: An Indicator of Clinical Communication Quality in Racially-Concordant and Racially-Discordant Oncology Interactions

Objectives The aim of this cross-sectional study was to apply a novel software to measure and compare levels of nonverbal synchrony, as a potential indicator of communication quality, in video recordings of racially-concordant and racially-discordant oncology interactions. Predictions include that the levels of nonverbal synchrony will be greater during racially-concordant interactions than racially-discordant interactions, and that levels of nonverbal synchrony will be associated with traditional measures of communication quality in both racially-concordant and racially-discordant interactions. Design This is a secondary observational analysis of video-recorded oncology treatment discussions collected from 2 previous studies. Setting Two National Cancer Institute-designated Comprehensive Cancer Centers and another large urban cancer center. Participants Participants from Study 1 include 161 White patients with cancer and 11 White medical oncologists. Participants from Study 2 include 66 Black/African-American patients with cancer and 17 non-Black medical oncologists. In both studies inclusion criteria for patients was a recent cancer diagnosis; in Study 2 inclusion criteria was identifying as Black/African American. Main outcome measures Nonverbal synchrony and communication quality. Results Greater levels of nonverbal synchrony were observed in racially-discordant interactions than in racially-concordant interactions. Levels of nonverbal synchrony were associated with indicators of communication quality, and these associations were more consistently found in racially-discordant interactions. Conclusion This study advances clinical communication and disparities research by successfully applying a novel approach capturing the unconscious nature of communication, and revealing differences in communication in racially-discordant and racially-concordant oncology interactions. This study highlights the need for further exploration of nonverbal aspects relevant to patient-physician interactions

OpenMx 2.0:Extended Structural Equation and Statistical Modeling

The new software package OpenMx 2.0 for structural equation and other statistical modeling is introduced and its features are described. OpenMx is evolving in a modular direction and now allows a mix-and-match computational approach that separates model expectations from fit functions and optimizers. Major backend architectural improvements include a move to swappable open-source optimizers such as the newly-written CSOLNP. Entire new methodologies such as Item Factor analysis (IRT) and State-space modeling have been implemented. New model expectation functions including support for the expression of models in LISREL syntax and a simplified multigroup expectation function are available. Ease-of-use improvements include helper functions to standardize model parameters and compute their Jacobian-based standard errors, access to model components through standard R $ mechanisms, and improved tab completion from within the R Graphical User Interface

Time to get personal? The impact of researchers choices on the selection of treatment targets using the experience sampling methodology:The impact of researchers choices on the selection of treatment targets using the experience sampling methodology

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 contingent on the researcher performing them. METHODS: To evaluate this, we crowdsourced the analysis of one individual patient’s ESM data to 12 prominent research teams, asking them what symptom(s) they would advise the treating clinician to target in subsequent treatment. RESULTS: Variation was evident at different stages of the analysis, from preprocessing steps (e.g., variable selection, clustering, handling of missing data) to the type of statistics and rationale for selecting targets. Most teams did include a type of vector autoregressive model, examining relations between symptoms over time. Although most teams were confident their selected targets would provide useful information to the clinician, not one recommendation was similar: both the number (0–16) and nature of selected targets varied widely. CONCLUSION: This study makes transparent that the selection of treatment targets based on personalized models using ESM data is currently highly conditional on subjective analytical choices and highlights key conceptual and methodological issues that need to be addressed in moving towards clinical implementation

The influence of expectation on spinal manipulation induced hypoalgesia: An experimental study in normal subjects

<p>Abstract</p> <p>Background</p> <p>The mechanisms thorough which spinal manipulative therapy (SMT) exerts clinical effects are not established. A prior study has suggested a dorsal horn modulated effect; however, the role of subject expectation was not considered. The purpose of the current study was to determine the effect of subject expectation on hypoalgesia associated with SMT.</p> <p>Methods</p> <p>Sixty healthy subjects agreed to participate and underwent quantitative sensory testing (QST) to their leg and low back. Next, participants were randomly assigned to receive a positive, negative, or neutral expectation instructional set regarding the effects of a specific SMT technique on pain perception. Following the instructional set, all subjects received SMT and underwent repeat QST.</p> <p>Results</p> <p>No interaction (p = 0.38) between group assignment and pain response was present in the lower extremity following SMT; however, a main effect (p < 0.01) for hypoalgesia was present. A significant interaction was present between change in pain perception and group assignment in the low back (p = 0.01) with participants receiving a negative expectation instructional set demonstrating significant hyperalgesia (p < 0.01).</p> <p>Conclusion</p> <p>The current study replicates prior findings of c- fiber mediated hypoalgesia in the lower extremity following SMT and this occurred regardless of expectation. A significant increase in pain perception occurred following SMT in the low back of participants receiving negative expectation suggesting a potential influence of expectation on SMT induced hypoalgesia in the body area to which the expectation is directed.</p

Theories, Methods, and Data: A Dance and a Conversation

Presented on January 30, 2019 at 3:00 p.m. in the J. S. Coon Building, Room 250.Dr. Steven M. Boker is Professor of Quantitative Psychology, Director of the Human Dynamics Laboratory, PI of the OpenMx SEM Software project, Speaker-Director of the UVA section of the International Max Planck Research School on the Life Course (LIFE), and Area Head of the Quantitative Psychology Area at the University of Virginia Department of Psychology.Runtime: 71:48 minutesThree dimensions of Cattell's persons by variables by time data box are discussed in the context of three types of researchers each wanting to answer their own categorically different question. The example of the well-known speed-accuracy tradeoff is used to illustrate why these exemplify three different categories of statistical question. A conceptual model is presented for the speed-accuracy tradeoff example that could account for cross-sectional between persons effects, short term dynamics, and long term learning effects. Two fundamental differences between the time axis and the other two axes of the data box include ordering and time scaling. In addition, nonstationarity in human systems poses a pervasive problem along the time dimension of the data box. To illustrate this, the difference in nonstationarity between dancing and conversation is discussed in the context of the interaction between theory, methods, and data. An information theoretic argument is presented that the theory-methods-data interaction is better understood when viewed as a conversation than as a dance. Entropy changes in the development of a theory-methods-data conversation provide one metric for evaluating scientific progress