Correlational Methods for Analysis of Dance Movements

December 17th, 2012

Brick, T. R. & Boker, S. M. (2011) Correlational Methods for Analysis of Dance Movements. Dance Research, Special Electronic Issue: Dance and Neuroscience: New Partnerships, 29:2, 283–304

We propose to present three methods for the exploration of symmetry and synchrony in motion-capture data as is it applied to dance and illustrate these with examples from a study of free-form dance. First, Generalized Local Linear Approximation (GLLA) provides a transformation from the positional data returned by such a system into a representation including approximations of velocity and acceleration. Using these newly transformed data, time-lagged autocorrelation can provide insight into the structure of temporal symmetry within a single person’s movements during the dance. Windowed cross-correlation can show other kinds of symmetry between individuals or between an individual and an outside stimuli, such as a rhythm or musical work. Combined, these techniques provide powerful tools for the examination of the structure of symmetry and synchrony in dance.

The manuscript of this article accepted for publication can be requested as a pdf file from the first author: Timothy Brick at the Max Planck Institute for Human Development.

OpenMx: An Open Source Extended Structural Equation Modeling Framework

December 17th, 2012

Boker, S. M., Neale, M., Maes, H., Wilde, M., Spiegel, M., Brick, T., Spies, J., Estabrook, R., Kenny, S., Bates, T., Mehta, P., & Fox, J. (2011) OpenMx: An Open Source Extended Structural Equation Modeling Framework. Psychometrika, 76:2, 306-317. NIHMS ID: 427396

OpenMx is free, full-featured, open source, structural equation modeling (SEM) software. OpenMx runs within the R statistical programming environment on Windows, Mac OS-X, and Linux computers. The rationale for developing OpenMx is discussed along with the philosophy behind the user interface. The OpenMx data structures are introduced — these novel structures define the user interface framework and provide new opportunities for model specification. Two short example scripts for the specification and fitting of a confirmatory factor model are next presented. We end with an abbreviated list of modeling applications available in OpenMx 1.0 and a discussion of directions for future development.

The manuscript of this article accepted for publication can be downloaded as a PDF. This article may not exactly replicate the final version published in Psychometrika. It is not the copy of record.

Time Delay Embedding Increases Estimation Precision of Models of Intraindividual Variability

December 17th, 2012

Oertzen, T. v. & Boker, S. (2010) Time Delay Embedding Increases Estimation Precision of Models of Intraindividual Variability. Psychometrika, 75:1, 158-175. NIHMS ID: 427398

This paper investigates the precision of parameters estimated from local samples of time dependent functions. We find that time delay embedding, i.e., structuring data prior to analysis by constructing a data matrix of overlapping samples, increases the precision of parameter estimates and in turn statistical power compared to standard independent rows of panel data. We show that the reason for this effect is that the sign of estimation bias depends on the position of a misplaced data point if there is no a priori knowledge about initial conditions of the time dependent function. Hence, we reason that the advantage of time delayed embedding is likely to hold true for a wide variety of functions. We support these conclusions both by mathematical analysis and two simulations.

The manuscript of this article accepted for publication can be downloaded as a PDF. This article may not exactly replicate the final version published in Psychometrika. It is not the copy of record.

Modeling Noisy Data with Differential Equations using Observed and Expected Matrices

March 23rd, 2010

Deboeck, P. R. & Boker, S. M. (in press) Modeling Noisy Data with Differential Equations using Observed and Expected Matrices. Psychometrika

Complex intraindividual variability observed in psychology may be well described using differential equations. It is difficult, however, to apply differential equation models in psychological contexts, as time series are frequently short, poorly sampled, and have large proportions of measurement and dynamic error. Furthermore, current methods for differential equation modeling usually consider data that are atypical of many psychological applications. Using embedded and observed data matrices, a statistical approach to differential equation modeling is presented. This approach appears robust to many characteristics common to psychological time series.

The manuscript of this article accepted for publication can be requested as a pdf file from the first author: Pascal Deboeck at University of Kansas.

Resilience-As-Process: Negative Affect, Stress, and Coupled Dynamical Systems

March 23rd, 2010

Montpetit, M. A., Bergeman, C. S., Deboeck, P. R., Tiberio, S. S., & Boker, S. M. (2010) Resilience-As-Process: Negative Affect, Stress, and Coupled Dynamical Systems. Psychology and Aging 25:3, 631-640

This article describes a link between stress and negative affect as a system of coupled linear differential equations. The idea is basically that stress and negative affect are coupled, but that those individuals with higher trait resilience scores would experience stress as being less coupled to changes in negative affect. In addition it was found that higher levels of social support resulted in greater damping of the fluctuations in negative affect and decreased coupling between stress and negative affect.

The manuscript of this article accepted for publication can be requested as a pdf file from the first author: Mignon Montpetit at Illinois Wesleyan University.

OpenMx Enters Public Beta Testing

October 7th, 2009

OpenMx entered public beta testing on October 8, 2009. The OpenMx website is now accepting self-registration. Go to the website, register, login, and download the most advanced free and open source Structural Equation Modeling package available. Registration also allows posting access to the OpenSem forums. Let us know what you think!

OpenMx is made possible by a Roadmap Initiative grant from the National Institutes of Health

Issues in Intraindividual Variability: Individual Differences in Equilibria and Dynamics over Multiple Time Scales

October 6th, 2009

Boker, S. M., Molenaar, P., & Nesselroade, J. R. (in press) Issues in Intraindividual Variability: Individual Differences in Equilibria and Dynamics over Multiple Time Scales. Psychology and Aging

This article expands on three methodological issues that address needs required to improve research in intraindividual variability: (1) The need to consider the relationship between the time scale of a process and the time scale of its measurement, (2) The need to first model both the deterministic and the stochastic components of psychological processes at the intraindividual level then at a second level model the variation in these deterministic and stochastic components in samples of individuals, and (3) The need to expand one’s thinking beyond individual differences in variance and covariance of latent variables given measurement invariance in order to consider the opposite possibility: idiosyncratic measurement models with invariance applied to the variance and covariance of latent variables.

The manuscript of this article accepted for publication can be downloaded as a PDF. This article may not exactly replicate the final version published in the APA journal. It is not the copy of record.

Parallel Workflows for Data Driven Structural Equation Modeling in Functional Neuroimaging

October 6th, 2009

Kenny, S., Andric, M., Boker, S. M., Neale, M. C., Wilde, M., & Small, S. L. (2009) Parallel Workflows for Data–Driven Structural Equation Modeling in Functional Neuroimaging. Frontiers in Neuroscience

This article presents 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 Core Development Team, 2008), consisting of self-contained structural equation models, 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.

Frontiers in Neuroscience is an open-access journal, so a PDF of the article can be downloaded for free.

Resilience in Adulthood Comes of Age

October 6th, 2009

Ong, A. D., Bergeman, C. S., & Boker, S. M. (2009) Resilience in Adulthood Comes of Age: Defining Features and Dynamic Conceptions. Journal of Personality. 77:6.

This article begins with a selective review of the broad literature on resilience, giving emphasis to the major approaches, empirical findings, and guiding principles that characterize prior studies. It then summarizes an approach to the phenomenon of resilience and illustrate select parts of previous and ongoing studies of older adults. Findings from this research add to the growing body of empirical evidence suggesting that resilience is a common phenomenon that emerges from the coordinated orchestration of basic human adaptive processes.

This article is previewed on the Journal of Personality website and will appear in the December issue. Unfortunately, Wiley/Blackwell rules would require us to pay at $3,000 fee if we were to either provide a downloadable copy or send a pdf as a response to a reprint request. However, since NIH funded parts of this work, Wiley/Blackwell is required to submit the final published version to pubmed. Hooray for NIH! When the free pubmed version is available, a link to that version will appear here.

Representing Time-Varying Cyclic Dynamics Using Multiple-Subject State-Space Models

September 17th, 2009

Chow, S.-M., Hamaker, E. L., Fujita, F. & Boker, S. M. (2009) Representing Time-Varying Cyclic Dynamics Using Multiple-Subject State-Space Models. British Journal of Mathematical and Statistical Psychology. vol 62, 683-716.

THis article compares two contemporary state-space models for dynamical systems analysis: the stochastic cycle model and the dynamic harmonic regression model. These models are applied to two studies: one on postural dynamics and another daily diary study of affect. Publication rules for BJMSP prohibit us from quoting excerpts or distributing the manuscript on the web, but we can send a reprint if you send one of the authors an email request.