Statistical Learning for the Spectral Analysis of Time Series Data

Spectral analysis of biological processes poses a wide variety of complications. Statistical learning techniques in both the frequentist and Bayesian frameworks are required overcome the unique and varied challenges that exist in analyzing these data in a meaningful way. This dissertation presents new methodologies to address problems in multivariate stationary and univariate nonstationary time series analysis. The first method is motivated by the analysis of heart rate variability time series. Since it is nonstationary, it poses a unique challenge: localized, accurate and interpretable descriptions of both frequency and time are required. By reframing this question in a reduced-rank regression setting, we propose a novel approach that produces a low-dimensional, empirical basis that is localized in bands of time and frequency. To estimate this frequency-time basis, we apply penalized reduced rank regression with singular value decomposition to the localized discrete Fourier transform. An adaptive sparse fused lasso penalty is applied to the left and right singular vectors, resulting in low-dimensional measures that are interpretable as localized bands in time and frequency. We then apply this method to interpret the power spectrum of HRV measured on a single person over the course of a night. The second method considers the analysis of high dimensional resting-state electroencephalography recorded on a group of first-episode psychosis subjects compared to a group of healthy controls. This analysis poses two challenges. First, estimating the spectral density matrix in a high dimensional setting. And second, incorporating covariates into the estimate of the spectral density. To address these, we use a Bayesian factor model which decomposes the Fourier transform of the time series into a matrix of factors and vector of factor loadings. The factor model is then embedded into a mixture model with covariate dependent mixture weights. The method is then applied to examine differences in the power spectrum for first-episode psychosis subjects vs healthy controls. Public health significance: As collection methods for time series data becomes ubiquitous in biomedical research, there is an increasing need for statistical methodology that is robust enough to handle the complicated and potentially high dimensionality of the data while retaining the flexibility needed to answer real world questions of interest

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Examining Effects of Arousal and Valence Across the Adult Lifespan in an Emotional Stroop Task

As age increases, there is evidence that people tend to pay less attention to negative information, pay more attention to positive information, or both. There are many theoretical accounts that attempt to explain this positivity bias. In the current study, I examined positivity effects across the adult lifespan by evaluating competing predictions of two theories: Socioemotional Selectivity Theory, which is based in motivation, and Dynamic Integration Theory, which is based in capacity. Computer mouse tracking was used to examine effects across levels of Valence (negative, neutral, and positive) and Arousal (low, medium, and high) in an emotional Stroop task. Participants were instructed to identify the ink color of each word, while ignoring word meaning. With increased age, participants responded faster and more efficiently to negative words relative to neutral words. Additionally, with increased age and EC (Emotional Complexity), participants’ responses were slower and more deviated for low arousing positive words relative to neutral words, consistent with SST. Furthermore, as age and EC increased, participants had faster initiation times (ITs) for low arousing negative words relative to neutral words, consistent with SST. The results contribute to a better understanding of emotional cognitive biases across the adult lifespan

An Experiment to Determine if Teacher Preparation in a Small High School Can be Reduced by Alternating Class Scheduling

The purpose of this study was to determine if by alternating certain classes biennially the number of different teaching preparations could be reduced thus decreasing the teachers\u27 load. The study also attempted to ascertain the effect this type of scheduling had upon the attitudes of teachers and students toward these classes. A further attempt was made to determine if mixing students from two grade levels resulted in the younger student being penalized with respect to his cumulative grade point average. The significant conclusions that can be drawn from the results follow: Teachers, generally, thought well of the project and desires to participate in it. Although some teachers expressed reservations about the project there were none that could not be removed by correcting the problems expressed. At the conclusion of the study most were in favor of continuing the project. By alternating classes biennially which were normally taught annually the class preparation load for teachers participating in the project was reduced and this basic quest of the project was, in fact, met. Students were not aroused unduly by the experimental nature of the project but sensed the need for long-range planning and increased guidance in setting up their schedules. They did not object to being combined with other grade levels in the project classes. Contrary to administrative expectations, however, the younger students did tend to receive lower marks in the project classes. Achievement progress as measured by the use of standardized tests revealed no significant difference between students in the experimental school and those students in the control school

The Effects of Talker Variability and Talkers\u27 Gender on the Perception of Spoken Taboo Words

In the current experiment, I examined the effects of inter-talker variability and talkers\u27 gender on listeners\u27 perception of spoken taboo words. Previous spoken word recognition research using the long-term repetition-priming paradigm, in which listeners respond to two separate blocks of spoken words, found performance costs for stimuli mismatching in talker identity. That is, when words were repeated across the two blocks and the identity of the talker remained the same (e.g., male to male) reaction times (RTs) were faster relative to when the repeated words were spoken by two different talkers (e.g., male to female). Such performance costs, or talker effects, followed a time course, occurring only when processing was relatively slow. More recent research has found that explicit and implicit attention towards the talker led to talker effects (even during relatively fast processing). The purpose of the current study was to examine how word meaning could affect the pattern of talker effects. Participants completed an easy lexical decision task and participants\u27 mean accuracy rates and RTs were analyzed. I hypothesized that hearing taboo words would surprise the listeners and grab their attention, such that talker effects are obtained even when processing is relatively fast. The results are consistent with the attention-based hypothesis that talker effects emerge when participants hear both spoken taboo and neutral words. However, talker effects emerged regardless of the talkers\u27 gender. In addition, taboo words were responded to faster than neutral words, suggesting that spoken word recognition can be affected by word meaning. The results of the current study have important implications for theoretical models of spoken word recognition and how attention plays a rol

Examining Effects of Arousal and Valence Across the Adult Lifespan in an Emotional Stroop Task

As age increases, there is evidence that people tend to pay less attention to negative information, pay more attention to positive information, or both. There are many theoretical accounts that attempt to explain this positivity bias. In the current study, I examined positivity effects across the adult lifespan by evaluating competing predictions of two theories: Socioemotional Selectivity Theory, which is based in motivation, and Dynamic Integration Theory, which is based in capacity. Computer mouse tracking was used to examine effects across levels of Valence (negative, neutral, and positive) and Arousal (low, medium, and high) in an emotional Stroop task. Participants were instructed to identify the ink color of each word, while ignoring word meaning. With increased age, participants responded faster and more efficiently to negative words relative to neutral words. Additionally, with increased age and EC (Emotional Complexity), participants’ responses were slower and more deviated for low arousing positive words relative to neutral words, consistent with SST. Furthermore, as age and EC increased, participants had faster initiation times (ITs) for low arousing negative words relative to neutral words, consistent with SST. The results contribute to a better understanding of emotional cognitive biases across the adult lifespan

A Descriptive Analysis of Eight Remedial Reading Students in the Sevier District Schools

Authorities have variously estimated the number of children with a reading disability to be between ten and fifteen percent of the total school population.1,2,3 Formerly, many children who had reading difficulties perhaps left school at an early age. Also, many children who might have had reading problems perhaps remained undetected before widespread group testing was initiated. Today, with the high premium placed upon high school and even college achievement, an education is, so to speak, a prerequisite to adult success. With reading unique in its being both a subject area and a tool necessary for the mastery of other subject areas, any disability is worthy of concern and consideration

Examining Effects of Arousal and Valence Across the Adult Lifespan in an Emotional Stroop Task

As age increases, there is evidence that people tend to pay less attention to negative information, pay more attention to positive information, or both. There are many theoretical accounts that attempt to explain this positivity bias. In the current study, I examined positivity effects across the adult lifespan by evaluating competing predictions of two theories: Socioemotional Selectivity Theory, which is based in motivation, and Dynamic Integration Theory, which is based in capacity. Computer mouse tracking was used to examine effects across levels of Valence (negative, neutral, and positive) and Arousal (low, medium, and high) in an emotional Stroop task. Participants were instructed to identify the ink color of each word, while ignoring word meaning. With increased age, participants responded faster and more efficiently to negative words relative to neutral words. Additionally, with increased age and EC (Emotional Complexity), participants’ responses were slower and more deviated for low arousing positive words relative to neutral words, consistent with SST. Furthermore, as age and EC increased, participants had faster initiation times (ITs) for low arousing negative words relative to neutral words, consistent with SST. The results contribute to a better understanding of emotional cognitive biases across the adult lifespan