A Multilevel Multivariate Analysis of Academic Performances in College Based on NCAA Student-Athletes

This is an application of contemporary multilevel regression modeling to the prediction of academic performances of 1st-year college students. At a first level of analysis, the data come from N > 16,000 students who were college freshman in 1994–1995 and who were also participants in high-level college athletics. At a second level of analysis, the student data were related to the different characteristics of the C = 267 colleges in Division I of the NCAA. The analyses presented here initially focus on the prediction of freshman GPA from a variety of high school academic variables. The models used are standard multilevel regression models, but we examine nonlinear prediction within these multilevel models, and additional outcome variables are considered. The multilevel results show that (a) high school grades are the best available predictors of freshman college grades, (b) the ACT and SAT test scores are the next best predictors available, (c) the number of high school core units taken does not add to this prediction but does predict credits attained, (d) college graduation rate has a second-level effect of a small negative outcome on the average grades, and (e) nonlinear models indicate stronger effects for students at higher levels of the academic variables. These results show that standard multilevel models are practically useful for standard validation studies. Some difficulties were found with more advanced uses and interpretations of these techniques, and these problems lead to suggestions for further research.     

Something in the way we move: Motion dynamics, not perceived sex, influence head movements in conversation

During conversation, women tend to nod their heads more frequently and more vigorously than men. An individual speaking with a woman tends to nod his or her head more than when speaking with a man. Is this due to social expectation or due to coupled motion dynamics between the speakers? We present a novel methodology that allows us to randomly assign apparent identity during free conversation in a video-conference, thereby dissociating apparent sex from motion dynamics. The method uses motion-tracked synthesized avatars that are accepted by naive participants as being live video. We find that 1) motion dynamics affect head movements but that apparent sex does not; 2) judgments of sex are driven almost entirely by appearance; and 3) ratings of masculinity and femininity rely on a combination of both appearance and dynamics. Together, these findings are consistent with the hypothesis of separate perceptual streams for appearance and biological motion. In addition, our results are consistent with a view that head movements in conversation form a low level perception and action system that can operate independently from top-down social expectations.     

Maternal depressive symptomatology and child behavior: transactional relationship with simultaneous bidirectional coupling

The present study investigated reciprocal relationships between adolescent mothers and their children's well-being through an analysis of the coupling relationship of mothers' depressive symptomatology and children's internalizing and externalizing behaviors. Unlike studies using discrete time analyses, the present study used dynamical systems to model time continuously, which allowed for the study of dynamic, transactional effects between members of each dyad. Findings provided evidence of coupling between maternal depressive symptoms and children's behaviors. The most robust finding was that as maternal depressive symptoms became more or less severe, children's behavior problems increased or decreased in a reciprocal manner. Results from this study extended upon theoretical contributions of such authors as Richters (1997) and Granic and Hollenstein (2003), providing empirical validation from a longitudinal study for understanding the ongoing, dynamic relationships between at-risk mothers and their children.     

A Conversation between Theory,Methods, and Data

The 10 year anniversary of the COGITO Study provides an opportunity to revisit the ideas behind the Cattell data box. Three dimensions of the persons × variables × time data box are discussed in the context of three categories 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 are three different categories of statistical question. The 200 persons by 100 variables by 100 occasions of measurement COGITO data cube presents a challenge to integrate theories and methods across the dimensions of the data box. 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. Thus, 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 is a pervasive problem along the time dimension of the data box. To illustrate, 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.     

Maintained Individual Data Distributed Likelihood Estimation (MIDDLE)

Maintained Individual Data Distributed Likelihood Estimation (MIDDLE) is a novel paradigm for research in the behavioral, social, and health sciences. The MIDDLE approach is based on the seemingly impossible idea that data can be privately maintained by participants and never revealed to researchers, while still enabling statistical models to be fit and scientific hypotheses tested. MIDDLE rests on the assumption that participant data should belong to, be controlled by, and remain in the possession of the participants themselves. Distributed likelihood estimation refers to fitting statistical models by sending an objective function and vector of parameters to each participant’s personal device (e.g., smartphone, tablet, computer), where the likelihood of that individual’s data is calculated locally. Only the likelihood value is returned to the central optimizer. The optimizer aggregates likelihood values from responding participants and chooses new vectors of parameters until the model converges. A MIDDLE study provides significantly greater privacy for participants, automatic management of opt-in and opt-out consent, lower cost for the researcher and funding institute, and faster determination of results. Furthermore, if a participant opts into several studies simultaneously and opts into data sharing, these studies automatically have access to individual-level longitudinal data linked across all studies.     

A MEASUREMENT OF THE ADAPTATION OE COLOR VISION TO THE SPECTRAL ENVIRONMENT

Abstract —An exploratory factor analysis of the reflectance spectral distributions of a sample of natural and man-made objects yields a factor pattern remarkably similar to psychophysical color-matching curves. The goodness-of-fit indices from a maximum likelihood confirmatory factor model with fixed factor loadings specified by empirical trichromatic color-matching data indicate that the human visual system performs near to an optimum value for an ideal trichromatic system composed of three linear components. An unconstrained four-factor maximum likelihood model fits significantly better than a three-factor unconstrained model, suggesting that a color metric is better represented in four dimensions than in a three-dimensional space. This fourth factor can be calculated as a nonlinear interaction term between the first three factors: thus, a trichromatic input is sufficient to compute a color space of four dimensions. The visual system may exploit this nonlinear dependency in the spectral environment in order to obtain a four-dimensional color space without the biological cost of a fourth color receptor.     

The Effect of Cancer on Suicide among Elderly Holocaust Survivors

Jewish‐Israelis of European origin with cancer have higher suicide rates relative to their counterparts in the general population. We investigated whether this effect results from the high proportion of Holocaust survivors among them, due to vulnerabilities arising from the earlier traumas they sustained. The study was based on all Jewish‐European persons with cancer, 60 years and over, diagnosed in Israel between 1999 and 2007. The standardized incidence ratios were not significantly different between the exposed and nonexposed groups (men: 0.90, 95% CI 0.60–1.19; women: 0.95, 95% CI 0.55–1.37). Past exposure to maximum adversity did not increase the suicide risk among persons with cancer.