Our QuantDev faculty, students, and collaborators frequently develop software in conjunction with methodological innovations.
This page collects links to Resources pages (where software can be downloaded) and related publications.Read More
The We R: R Users @ Penn State meet-ups provide an interdisciplinary work space, discussion and presentation forum for Penn State graduate students (undergraduates, postdocs, faculty, staff, etc. also welcome) who use (or would like to learn) R for science. Members come from a diverse range of departments including but not limited to HDFS, communication, psychology, biology, nutrition, statistics, political science, demography, geography, and sociology. Those of all skill levels are encouraged to attend.
The general structure involves a reserved weekly space for members to come as they please…Read More
One common problem in longitudinal studies is the presence of missing data. Intensive longitudinal data involving repeated assessments of constructs such as emotions are particularly prone to nonignorable missingness, namely, missingness where the missing data mechanism depends on unobserved information. For example, in measuring day-to-day changes in negative emotions, it is possible that the participants may opt not to report their feelings on the days with heightened negative emotions, thereby leading to nonignorable missingness when modeling emotion processes. Even though myriad…Read More
Infant sleep is an important aspect of infancy. Its influence extends into later years of child development and across various domains, including cognitive, emotional, and behavioral development. High-quality sleep in the first few years of life also lays the foundation for healthy sleep habits later on. Recent advances in technology have provided new opportunities and tools for collecting intensive longitudinal measurements of sleep quality in ways that are not intrusive to daily life. We are using dynamic system modeling techniques to analyze nighttime actigraphy (movement) data and explore…Read More
The Intraindividual Study of Affect, Health and Interpersonal Behavior is an intensive longitudinal study that collected rich repeated measures of its namesake variables at multiple time-scales. Participants, 150 adults (age 18-89 years, 51% women) from the Pennsylvania State University and surrounding community, completed three 3-week "measurements bursts" during which they reported on their social interactions, thoughts, feelings, and behaviors. Innovative study design that combined use of smartphone-based and web-based assessments provided rich data on behavior that unfolds across, hours,…Read More
With survival analysis, the most widely-used model is Cox's (1972) proportional hazard model. However, cancer control organizations and researchers using cancer registry data most often fit relative survival models. These models estimate survival in a hypothetical world where cancer is the only cause of mortality. This language arouses curiosity. We wondered whether it was used in the original 1961 cancer monograph and whether it is used now as simple shorthand because at no time in the past or in the future will we experience a world where cancer is the only cause of mortality. Cancer…Read More
Intensive longitudinal measurement designs prominent in econometrics, engineering, biophysics and brain imaging are also quickly coming to the forefront in psychology. Vector autoregressive models (VARs), often in combination with Granger causality testing, are often used in statistical analysis of time series data. Granger causality testing is used to establish the network of effective dynamic connections underlying the data. Yet, for each given data set there exist different versions of VARs that are statistically equivalent (i.e., yield exactly the same fit to the data and are related to…Read More
Social interaction is an important part of everyday life, but it is difficult to study in an ecologically valid environment. The goals of this project are to integrate scientific know-how about social interaction, physiology, and overall well-being into a unified platform for social and behavioral wellness. We are developing and testing a smartphone app that uses commodity wearable hardware to provide actionable feedback to the user on the physiological changes enacted by their day-to-day behaviors, especially in the context of social interactions. Specifically, the app will use state-of-the-…Read More
Co-robots are robots that work side-by-side with humans, assisting them and adapting to their needs rather than operating as isolated entities. Emotional states, such as frustration, and engagement play a constant part in performance of everyday tasks. A student who is overly stressed or distracted may commit errors that would be otherwise easy to avoid. We are developing Pennie, an educational co-robotic system sensitive to the emotional state of the humans it interacts with. Pennie is being developed to work with students as they learn to use the machinery in an engineering classroom. She…Read More
Conversational rapport refers to a close and harmonious relationship in which the people or groups involved understand each other's feelings and ideas and engage in effective communication, which leads to better quality relationships in the classroom or the workplace. This project is interested in using computer vision and computational linguistics technologies to understand how synchrony, symmetry, nonverbal behavior, and a variety of inter- and intra-personal measures interact to create (or fail to create) rapport in a dyad.Read More
This research study aims to improve the ability of individuals to use patient-supported online forums to obtain useful information for their personalized concerns. To do so, we are:
Developing a set of new search tools that collect information posted by individuals related to the management and care of Irritable Bowel Syndrome (IBS) on a patient-supported online forums; and
Personalizing the information for potential patients and users in a way that adapts to their particular ethnic and demographic background, clinical symptoms, etc.
Building navigational tools that will help users to…Read More
Irregularly spaced longitudinal data have become increasingly prevalent in empirical studies. In the study of human emotions, researchers often adopt ecological momentary assessment (EMA) procedures to obtain responses at random or event-contingent time intervals. Such designs facilitate the collection of data that reflect an individual's ongoing emotional states “in the moment." Common approaches based on ordinary and stochastic differential equations can be used to accommodate the irregular time intervals observed in such data, but they are not directly suited for handling the noisy, high-…Read More
The past several decades have seen the rise of intensive longitudinal data (e.g. via ecological momentary assessments) and the resulting dynamic modeling methods in social and behavioral sciences. To make the estimation of these models more accessible to researchers, we have created an R package that is based on a novel and efficient state-space estimation algorithm in C. This is a demo of the beta version of the dynr R package: an R package that utilizes computationally efficient algorithms for a broad class of dynamic models that are increasing in use while maintaining a simple and easy-to-…Read More
Computational modeling is central to a rigorous understanding of the development of the child’s first social relationships. The project addresses this challenge by modeling longitudinal change in the dynamics of early social interactions. Our proposed models integrate objective (automated) measurements of emotion and attention and common genetic variants relevant to those constructs. This project is supported by funding from the National Institute of General Medical Sciences.
Selected products/outcomes from this project
Workshops and demos:
Cohn, J.F. (March 2015). Face processing.…Read More
This project is focusing on the merging of intraindividual variability (IIV) methods and network methods and applying this fusion method on intensive longitudinal studies. We used a two-stage approach to accomplish this. The first stage is to construct a high-dimensional person-specific network structure using IIV method and the second stage is to use network methods to examine the characteristic and measure change of this person-specific network. So far, we have found empirical evidence that impact of major life events (e.g. divorce, illness, etc) is associated with density of a…Read More
The BeingWellProject is a research project in which we re-imagine well-being as a complex dynamical system. By combining cognitive psychometric techniques and dynamical systems modeling, the goal is to unpack the mechanisms, pathways, and synchronicity dynamics of emotional and cognitive elements of well-being. We conduct ecological momentarily assessment studies in which participants report on their well-being while living their everyday life. Moreover, we are also interested in studying how these well-being elements synchronize with physiological measures, such as blood volume pulse and…Read More
The availability of mobile real-time data streams (e.g., laptops, smart phones, etc.) make this an exciting time. These new data are allowing us to re-conceptualize how we live, learn, communicate, and organize our daily lives to achieve personal goals. This project is about the interdependence of behavior across multiple domains (school, health, leisure), multiple time-scales (days, months), and multiple spatial/virtual locations (classroom, gym, home, games, media). We focus on the individual – the quantified self – as a complex system that exchanges data with many different data archives.…Read More
Self-regulation is a core construct in health research due to its relation to a broad array of child and adult health problems, such as obesity, mental disorders, and heart disease. The breadth of evidence implicating self-regulation in health emerged from varied approaches to its definition and examination. Our work addresses the basic scientific need for greater consistency and integration in how self-regulation is conceptualized, modeled, and measured.
At their core, multiple theoretical perspectives approach self-regulation as the engagement of executive psychological processes to alter…Read More
Family and dynamic systems theories have emerged from basic principles of general systems theory (von Bertalanffy, 1968). In this project we are exploring how the modeling frameworks being used in ecology (nonlinear dynamic models) can be used to study family systems. First, we review some of the theoretical principles at the core of dynamic systems theory that can be applied to the study of families. Second, we briefly summarize how the taxonomies used in biological ecology to describe interspecies interactions (e.g., symbiosis) have been articulated using the general mathematical framework…Read More
Asthma requires daily monitoring of lung function, which can be affected by variations in medication usage, in addition to a number of different behaviors and triggers. Problems associated with an inappropriate type or dosage level of medication are especially important. Despite our recognition of the variability in patients’ responses to various types of medications and dosage levels, little has been put into place that would monitor a patient’s responses to medication in a continuing way so that proper adjustments can be made for the duration of the use of that drug therapy. The…Read More