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Uzdavines, AlexStressful Events and Religious Identities: Investigating the Risk of Radical Accommodation
Master of Arts, Case Western Reserve University, Psychology
At some point in their lives, everyone will experience a stressful life event. Usually, someone can cope with and make meaning from the event. However, the body of research investigating the impact of severe and/or chronic exposure to stressful life events on the brain shows that harmful effects of stress exposure accumulate. Considering the extant literature regarding religious meaning making in light of these findings and the robust literature on spiritual transformation following stressful life events, I developed three hypotheses: 1) stressful life events increase risk of (non)religious ID change, 2) earlier events continued to impact later ID changes, and 3) risk of ID change was similar across change groups. This study analyzed a nationally representative longitudinal dataset of US children born between 1980 and 1984 (N = 8984). The final analyses used multiple imputation to account for missing data and did not find evidence supporting the hypotheses.

Committee:

Julie Exline, Ph.D. (Committee Chair); Heath Demaree, Ph.D. (Committee Member); Arin Connell, Ph.D. (Committee Member)

Subjects:

Health; Mental Health; Psychology; Religion; Spirituality

Keywords:

stressful life events; conversion; atheism; religion; spirituality; missing data analysis; multiple imputation by chained equations; longitudinal; national longitudinal survey of youth; meaning making; open science

Sucheston, Lara E.STATISTICAL METHODS FOR THE GENETIC ANALYSIS OF DEVELOPMENTAL DISORDERS
Doctor of Philosophy, Case Western Reserve University, 2007, Epidemiology and Biostatistics
This dissertation focuses on approaches to the genetic analysis of longitudinal measures of developmental disorders (DD) with specific application to a longitudinal pedigree study of children ascertained on the basis of a Speech Sound Disorder (SSD). Analysis of this longitudinal cohort is complicated by non-normal trait distributions and a potentially non-linear cognitive developmental trajectory. Prior to developing a longitudinal model I measured the power of the SSD dataset to correctly detect linkage of a quantitative trait to a genetic marker. Assuming that the function describing the genetic effect across time is correctly specified the power of the SSD data set is .18 at a .01 level of signficance. Additional data collection is planned and by doubling the sample size (from 200 to 400 sibling pairs) and number of measurement points (from 2 to 4) the power increases to .83 for the same significance level. It is therefore reasonable to develop a longitudinal approach for use at a later date. As an alternative to the longitudinal analysis, multivariate dependence functions, called copulas, are used to develop a cross-sectional model to test for polygenic*age interaction. These functions separate a multivariate joint distribution into two parts: one describing the interdependency of the probabilities (correlation), the other describing the distribution of the margins (the phenotypes). Using these functions for analysis simultaneously addresses both the non-normality problem, as the margins can be modeled with a wide variety of parametric probability distributions and the developmental trajectory question, as we incorporate age into the analysis through the use of a correlation function, the parameter estimate of which can be tested for significance using a chi-square test statistic. Four of the 13 SSD test measures showed nominal p-values less than .05. While at the broadest level the 4 tests measure different cognitive skills, short term memory plays an important role in each of these tests. This provides preliminary evidence that the genetic contribution to phenotypic variance of tasks involving memory is not stationary in children ages 6 to 18.

Committee:

Sudha Iyengar (Advisor)

Subjects:

Statistics

Keywords:

speech sound disorder; longitudinal model; gene age interaction; longitudinal copula model

Mattei, Gina MarieChildhood Precursors of Adult Social Capital Indices
Master of Arts (MA), Bowling Green State University, 2015, Psychology/Clinical
Objective. Social capital is generally defined as an individual’s potential for tangible or social resources made available via interpersonal connections. Higher levels are related to a variety of positive health, well-being, and occupational outcomes. Social capital can be measured by a variety of indices in adulthood. Currently, the childhood precursors to adult social capital are relatively unknown. The current project tests a developmental-contextual model for both the measurement of social capital in adulthood and the childhood precursors that may impact its accumulation over the life course. Methods. 523 participants were surveyed at age 8 and again at age 48 as part of a 40-year prospective, longitudinal study. Participants completed measures of cognitive abilities, relationships with parents, peers, and spouses, information about personal traits, and beliefs and attitudes regarding social relationships. Structural Equation Modeling (SEM) was used to test the hypothesized model. Results. The proposed measurement model of social capital was generally supported, with latent domains of individual, interpersonal, socio-economic, and community level indices. Predictive models of childhood precursors for social capital differed by gender: prominent precursors were childhood aggression and cognitive ability for males, and childhood family religiosity for females. Conclusions. These findings suggest that a developmental-contextual model of social capital may account for the multiple indices of social capital and that its accumulation across the life course is different for males and females. Knowledge of precursors may be clinically helpful for fostering social capital growth in therapeutic settings.

Committee:

Eric Dubow, Ph.D. (Advisor); Carolyn Tompsett, Ph.D. (Committee Member); Marie Tisak, Ph.D. (Committee Member)

Subjects:

Clinical Psychology

Keywords:

social capital; developmental-contextual model; ecological model; longitudinal; structural equation modeling; Columbia County Longitudinal Study

Henderson, Alexandra ARole overload and health behaviors: Demonstrating adaptation longitudinally
Master of Arts (MA), Bowling Green State University, 2015, Psychology/Industrial-Organizational
Longitudinal approaches to studying the stressor-strain relationship, using theories like adaptation, have received increased attention in the literature. However, only psychological responses have been studied within the adaptation theory framework. As such, this study examines the adaptability of health behaviors (sleep quality, diet quality, and physical activity) in response to role overload in order to bridge this gap in the adaptation literature and provide insight into the dynamic relationship between workplace stressors and health behaviors. Participants (n = 520) completed five surveys, with one-month lags between assessments. Path analytic results indicate that people’s health behaviors are negatively influenced by experiences of role overload within each time point; however, health behaviors adapt, or regress to previous levels, over time. Yet, the adaptation processes of the health behaviors did appear to differ, as sleep quality continued adapting to an experience of role overload across all time points, whereas diet quality and physical activity only demonstrated adaptation after one month. Results also suggest that sleep quality influences future experiences of role overload, such that poor sleep will make individuals more susceptible to future experiences of role overload. Theoretical and practical implications, as well as study limitations, are also discussed.

Committee:

Russell Matthews (Advisor); Steve Jex (Committee Member); Yiwei Chen (Committee Member)

Subjects:

Psychology

Keywords:

adaptation; role overload; health behavior; sleep; diet; physical activity; longitudinal

Gordon, Diandra ReneeChildhood Exposure to Intimate Partner Violence and Socioemotional Development from Early to Middle Childhood
Master of Science, The Ohio State University, 2015, Human Ecology: Human Development and Family Science
Intimate partner violence (IPV) is a preventable health problem that has multiple effects on the family, including the youngest member of the family, the child. For many years children were not recognized as having detrimental consequences of IPV. Now that it is recognized that children suffer from the negative effects of IPV, it is important to examine how and when exposure to IPV is associated with the development of children. This study uses the Fragile Families and Child Wellbeing study to examine the socioemotional development of children exposed to IPV from birth to 9 years old. Using structural equation modeling, latent growth curve models were conducted to analyze internalizing and externalizing problems at age 3, 5, and 9. Children who were exposed to IPV, whether it be a violent and controlling or a controlling only relationship, had more internalizing and externalizing problems. Also, the earlier and longer the child was exposed to IPV, the more socioemotional problems the child had. Identifying the critical time period of externalizing and internalizing problems for children exposed to IPV is crucial for intervention techniques and child victims’ long-term development. Every child should be able to develop to their fullest potential, by targeting intervention efforts at those critical time points, it could allow for children to live up to their full promise.

Committee:

Claire Kamp Dush, PhD (Advisor); Sarah Schoppe-Sullivan, PhD (Committee Member)

Subjects:

Demography; Developmental Psychology; Early Childhood Education; Families and Family Life

Keywords:

intimate partner violence; domestic violence; family violence; child outcomes; longitudinal; child development; fragile families and child well-being; demography

Gunbatar, YakupNonlinear Adaptive Control and Guidance for Unstart Recovery for a Generic Hypersonic Vehicle
Doctor of Philosophy, The Ohio State University, 2014, Electrical and Computer Engineering
This work presents the development of an integrated flight controller for a generic model of a hypersonic air-breathing vehicle. The flight control architecture comprises a guidance and trajectory planning module and a nonlinear inner-loop adaptive controller. The emphasis of the controller design is on achieving stable tracking of suitable reference trajectories in the presence of a specific engine fault (inlet unstart), in which sudden and drastic changes in the vehicle aerodynamics and engine performance occur. First, the equations of motion of the vehicle for a rigid body model, taking the rotation of the Earth into account, is provided. Aerodynamic forces and moments and engine data are provided in lookup-table format. This comprehensive model is used for simulations and verification of the control strategies. Then, a simplified control-oriented model is developed for the purpose of control design and stability analysis. The design of the guidance and nonlinear adaptive control algorithms is first carried out on a longitudinal version of the vehicle dynamics. The design is verified in a simulation study aiming at testing the robustness of the inner-loop controller under significant model uncertainty and engine failures. At the same time, the guidance system provides reference trajectories to maximize the vehicle's endurance, which is cast as an optimal control problem. The design is then extended to tackle the significantly more challenging case of the 6-degree-of-freedom (6-DOF) vehicle dynamics. For the full 6-DOF case, the adaptive nonlinear flight controller is tested on more challenging maneuvers, where values of the flight path and bank angles exceed the nominal range defined for the vehicle. Simulation studies show stable operation of the closed-loop system in nominal operating conditions, unstart conditions, and during transition from sustained scramjet propulsion to engine failure mode.

Committee:

Andrea Serrani, Prof. (Advisor); Umit Ozguner, Prof. (Committee Member); Zhang Wei, Prof. (Committee Member)

Subjects:

Aerospace Engineering; Computer Engineering; Electrical Engineering; Engineering

Keywords:

Hypersonic; unstart; adaptive control; nonlinear control; adaptive backstepping; trajectory optimization; optimal; tuning functions; longitudinal; 6-DOF; 3-DOF; Earth rotation; Control design model; coordinated turn; endurance; Equations of motion

Divaratne, Dilupama A.One and Two Neutron Removal Cross Sections of 24O via Projectile Fragmentation
Doctor of Philosophy (PhD), Ohio University, 2014, Physics and Astronomy (Arts and Sciences)
The objective of this research work is to study the ground state wavefunction of 24O, building on recent work conducted on this topic by various experimentalists and theorists. The ultimate goal is to determine how exactly doubly magic 24O is. Motivated by observations and guided by theoretical perspectives applicable to the nuclear structure of neutron-rich isotopes, the cross section and related spectroscopic factors of di erent final states in 23O are determined to investigate the ground state wave function of 24O. The experiment was conducted at the National Superconducting Cyclotron Laboratory at Michigan State University using the S800 spectrograph and a 470-mg/cm2 Be reaction target with 92.3-MeV/u 24O beam energy. The neutron knockout cross section of 24O to the 1/2+ ground state of 23O and two neutron removal cross section to 22O were measured. The cross section values to the di erent final states of 23O along with the related spectroscopic factors convey to us the composition of the 24O ground state wave function and eventually the magicity of it. Specific details of the experiment, the analysis carried out, and the interpretation of the measured knockout cross sections and longitudinal momentum distributions of residual nuclei are discussed herein

Committee:

Carl Brune (Advisor)

Subjects:

Nuclear Physics

Keywords:

Heavy Oxygen Isotopes; Neutron removal cross sections; NSCL experiments using S800 spectrograph; 24O ground state wave function; A1900 fragment separator; Longitudinal momentum distributions of heavy oxygen

Hauser, Bradley K.The Volunteers of Ohio Collaborative Watershed Groups, Yesterday and Today: Motivations, Activities, and Demographics
Master of Science, The Ohio State University, 2010, Natural Resources
A growing body of literature in collaborative natural resource management has identified factors associated with group processes, outputs, and outcomes. However, the majority of research is cross-sectional and does not permit the exploration of change over time, a significant knowledge gap considering the potential dynamic nature of these organizations. The current research examines longitudinal change in collaborative watershed groups by comparing the current participation trends of eleven Ohio groups to data collected five years earlier. While this contributes to a broader understanding of volunteer participation, to date, the variables that affect whether, why, and how volunteers participate have been analyzed in isolation. Although models have been developed across a broad array of disciplines in efforts to explain human behavior, many of these have not yet been applied to the study of participation in collaborative watershed groups. Among these models is the Theory of Planned Behavior. In the interest of building an interdisciplinary understanding of participation in collaborative watershed groups, this research examines variables from the Theory of Planned Behavior and volunteerism literature. Results from member surveys and interviews with watershed group leaders indicate both patterns and shifts in participation as collaborative groups mature, and highlight the importance of social factors in influencing participation.

Committee:

Tomas Koontz, PhD (Advisor); Joseph Bonnell, PhD (Committee Member); Jeremy Bruskotter, PhD (Committee Member); John Heywood, PhD (Committee Member)

Subjects:

Environmental Science; Social Research

Keywords:

collaborative watershed groups; longitudinal; participation; volunteerism; Theory of Planned Behavior

Sawant, Neil RavindraLongitudinal Vehicle Speed Controller for Autonomous Driving in Urban Stop-and-Go Traffic Situations
Master of Science, The Ohio State University, 2010, Electrical and Computer Engineering
In this thesis, we have addressed the issue of road congestion due to increased traffic in urban and metropolitan areas and have designed an autonomous longitudinal speed controller as a solution to this problem. One of the best ways to increase efficiency of the available road infrastructure is to enable vehicles to move in a platoon with very small distance headway from the preceding vehicle. We have developed a Longitudinal Finite State Machine which acts as a supervisory control to help the following vehicle to merge behind and follow the preceding vehicle. We have studied the performance of two vehicle following controllers, i.e. LQR based full-state feedback controller and LQR based sequential-state feedback controller, which are enabled and take the control of the vehicle velocity during the “follow” state of the vehicle’s Longitudinal FSM. A comparison analysis has been presented between the two controllers which help in reducing the distance headway from the preceding vehicle as well as maintaining string stability within the platoon.

Committee:

Umit Ozguner, PhD (Advisor); Kevin Passino, PhD (Committee Member)

Subjects:

Automotive Materials; Electrical Engineering; Engineering; Transportation

Keywords:

Longitudinal Vehicle Speed Control; LQR; Feedback Control; Convoy; Platoon; NSF; GCDC; Sequential State Feedback; Full State Feedback; Vehicle Modelling; V2V

Al-Shaikh, EnasLongitudinal Regression Analysis Using Varying Coefficient Mixed Effect Model
PhD, University of Cincinnati, 2012, Medicine: Biostatistics (Environmental Health)
Linear and nonlinear mixed models are very powerful techniques for modeling the relationship between a response variable and covariates and for handling the within-subject correlations in longitudinal data. For many applications in real life, however, it is difficult to find the proper parametric model to fit the data. Therefore, the adequacy of the model assumptions and the potential consequences of model misspecifications on the analysis under the classical linear model framework are questionable. Thus, it is important to increase the flexibility of linear regression models and to relax the conditions imposed on traditional parametric models to explore the hidden structure. The varying coefficient model (VCM), which was proposed by Hastie and Tibshirani (1993), provides a versatile and flexibale analysis tool for relating longitudinal responses to longitudinal predictors. Specically, this approach provides a novel representation of varying coefficient functions through suitable covariance of the underlying stochastic processes, which is particularly advantageous for sparse and irregular designs, as often encountered in longitudinal studies. In this dissertation, we hypothesized that varying coefficient mixed effect model (VCMEM) accurately predict, explore and address the relationship between four different covariates and the antigen level of MsgC using penalized spline smoothing technique. The longitudinal data were obtained from the Multicenter AIDS Cohort Study (MACS). We have two specific aims to test this hypothesis. The first aim is to fit VCMEM to MACS data, where the variable antigen level of MsgC is continuous. The second aim is to perform goodness of fit test to investigate the significance of the model covariates in VCMEM in the first aim using bootstrap techniques. We focused on fitting the VCMEM for the MACS data, where both fixed and random effects were modeled non-parametrically with P-spline smoothing. This allows us to explore how the effects of the covariates such as Prophylaxis treatment vary with time. In addition, mixed effect model captured the features of the individual profiles. Finally, we successfully demonstrated that the use of VCMEM for the MACS data provided an accurate analysis that describes the dynamic and structure of change and addresses the relationship between covariates such as the age at first AIDS define illness, at least one PcP episode before the death, taking Prophylaxis and the geographical location on the antigen level of MsgC. Based on our results, we concluded that the VCMEM fits the data better than the Linear mixed effect model (LME) models.

Committee:

Linda Levin, PhD (Committee Chair); Charles Ralph Buncher, ScD (Committee Member); Paul Succop, PhD (Committee Member); Peter Walzer, MD MSc (Committee Member)

Subjects:

Biostatistics

Keywords:

varying coefficient functions;longitudinal data;penalized spline smoothing;;;;

Chen, ChenBayesian Analyses of Mediational Models for Survival Outcome
PhD, University of Cincinnati, 2011, Arts and Sciences: Mathematical Sciences
This dissertation focuses on Bayesian mediation analysis for survival outcome. It consists of three parts. The first part of this dissertation is Bayesian semi-parametric mediation analysis for survival outcome with incomplete mediator. This work extends (Huang et al., 2004) approach to causal mediation analyses, addresses model misspecification problem that was inherited in the commonly used method (Lin et al., 1997); in addition, it solves the issues of missing mediator under the assumption of MCAR or MAR. The second part considers the problem of assessing mediation effect when both outcome and mediator are censored. This problem is tackled by developing an informative missing data imputation modeling for the censored mediator, and develop a Markov Chain Monte Carlo algorithm to obtain posterior estimates. The third part considers longitudinal mediator problem. The previous work (Taylor et al., 1998, 2001) is extended on joint modeling of longitudinal mediator and the survival outcome. For the longitudinal modeling of mediator, the proposed model considers fixed effects, random effects, and a specified stochastic process with measurement error using Dirichlet process priors on the coefficient parameters.

Committee:

Siva Sivaganesan, PhD (Committee Chair); Bin Huang, PhD (Committee Member); James Deddens, PhD (Committee Member); Paul Horn, PhD (Committee Member)

Subjects:

Mathematics

Keywords:

Bayesian;Mediation;Survival Outcome;Incomplete;longitudinal

Kourea, LefkiEffects of a supplemental reading intervention package on the reading skills of English speakers and English language learners in three urban elementary schools: A follow-up investigation
Doctor of Philosophy, The Ohio State University, 2007, Physical Activity and Educational Services
This study investigated the effectiveness of a supplemental early reading intervention package on the segmentation, blending and oral reading fluency skills of 23 urban first-grade students, including English Language Learners (ELLs), who continued to be at reading risk after receiving intensive phonological awareness training the previous year in kindergarten (i.e., ERI-Treatment Group). Additionally, the study examined the growth rates of 15 first-grade students, who reached benchmark status at the end of the previous year’s kindergarten intervention (i.e., ERI-Comparison Group), as well as the growth rates of 23 first-grade comparison students, identified the previous year in kindergarten with few or no markers of reading risk (i.e., Comparison Group). Six instructional assistants received a six-hour training package to deliver the intervention to the ERI-Treatment Group across three urban high poverty schools. Pre- and posttest standardized measures (WJ-III; CTOPP) and tri-weekly progress monitoring data were collected to evaluate student progress. Supplemental intervention was delivered 4-5 times per week for 20 to 30 minutes each session over a period of 57 to 88 sessions. Treatment integrity checks were collected frequently during random school visits. Measures of social validity were collected to evaluate direct consumers’ satisfaction about the goals, procedures and outcomes of the treatment. Data were analyzed with regression models, contrasts, and repeated measures mixed-effects modeling. Results showed that the ERI-Treatment group made substantial gains in phonological awareness and alphabetic understanding skills. Fewer gains were found in oral reading fluency and comprehension, especially for ELLs. The ERI-Comparison Group not only maintained treatment gains from the previous year’s intervention, but also performed comparably to the levels of their initially higher performing peers (Comparison Group). These findings highlight the importance of intensive phonological awareness training and its potentially lasting effects to reduce the reading risk of extremely vulnerable students. They also underscore the need to provide ongoing intensive support, depending on students’ responsiveness to intervention.

Committee:

Gwendolyn Cartledge (Advisor)

Subjects:

Education, Special

Keywords:

early reading interventions; longitudinal studies; urban learners; english language learners

Walters, Kimberly AnnThe Use Of Post-Intervention Data From Waitlist Controls To Improve Estimation Of Treatment Effect In Longitudinal Randomized Controlled Trials
Doctor of Philosophy, The Ohio State University, 2008, Biostatistics

In medicine and public health research, the randomized delayed-intervention controlled trial (RDICT), also known as a wait-listed or stepped wedge design, is commonly used to study overt, slow-acting treatments in comparison to a control condition over time. Ten RDICT designs are specified as generalizations of the motivating example, a longitudinal psychology study of a psychoeducational intervention for children with bipolar disorder. These designs vary according to number of observation occasions, time between observations, and length of delay before the control group receives treatment.

Two estimators of fixed effects in separate linear mixed effects (LME) models, θ1 and θ2, are proposed to measure treatment effect based on data from an RDICT design. The LME models have a piecewise linear mean structure, allowing phases for treatment, placebo, and leveling-off effects. The treatment effect is traditionally conceptualized as the difference in slopes between the immediate treatment (IT) and pre-intervention control groups, which we call θ1.

Alternately, in an RDICT design, the treatment effect can be the change in slope post-intervention in the delayed-treatment (DT) control group, called θ0. The full model, which allows these treatment effects to differ, produces the standard estimator, θ1. A reduced model, nested within the full one, forces the inter and intra treatment effects to be identical and produces the novel estimator, θ2.

A simulation study was conducted to observe the relative efficiency of θ2 to θ1 as it varies over the 10 RDICT designs and 8 scenarios, which differ in size of treatment effect, intraclass correlation, and sample allocation to DT group.

The best-performing and recommended RDICT design, called H2.5 with a DT:IT allocation ratio of 2:1, achieved a relative efficiency of 1.3 when the group-specific treatment effects are identical. The H2.5 design has the longest overall calendar duration of the 10 designs considered and is an extension of the design used in the motivating example study of childhood mood disorders.

Committee:

Joseph Verducci (Advisor); Haikady Nagaraja (Committee Member); William Notz (Committee Member)

Subjects:

Behaviorial Sciences; Biostatistics; Design; Health; Mental Health; Psychology; Public Health; Statistics; Therapy

Keywords:

longitudinal method; design; randomized controlled trials; treatment effect; intervention studies; repeated measures

Belagod, Trivikram SrinivasanALTERNATING LONGITUDINAL WEDGED COULOMB FORCES MINIMIZE TRANSVERSE TUBE VIBRATIONS THROUGH NON-LINEAR COUPLING
Master of Sciences (Engineering), Case Western Reserve University, 2009, EMC - Mechanical Engineering
The damping force and the self-excited force, which are a part of Heat Exchanger tube vibrations, act in the same (transverse) direction. The wedging process introduces alternating longitudinal coulomb forces that act at double the frequency of transverse vibrations and is defined by the wave equation. The transverse vibrations and the alternating longitudinal coulomb forces are coupled and act orthogonal to each other. Physical observations show that the transverse vibrations cannot exist without longitudinal vibrations. The governing constitutive equations for coupling can be shown theoretically through material non-linearities by considering higher order terms for the elastic energy, and geometric non-linearities by considering non-linear strain displacement relations. This non-linear constitutive equation when used in the equation of motion for transverse vibrations, the Gol’dberg tensorial result emerges. Energy reorganization due to this coupling results in reduced transverse vibration amplitudes. A simple experimental setup simulating this wedging process validates that transverse vibrations cannot occur without longitudinal vibrations.

Committee:

Joseph Mansour (Advisor); Winston Perera (Committee Co-Chair); Vassilis Panoskaltsis (Advisor); Joseph Prahl (Committee Member); Roger Quinn (Committee Member)

Subjects:

Engineering

Keywords:

heat exchanger;vibration;damping;self preloading;wedging;non linear coupling;heat exchanger tubes;transverse vibration;longitudinal vibration

Nicodemo, PhilipLongitudinal variation in the axial muscles of snakes
MS, University of Cincinnati, 2012, Arts and Sciences: Biological Sciences
The axial muscles of snakes are notable for having long tendons within individual segments that span several vertebrae. Consequently, muscles that extend anteriorly have a constraint on their length as their origins are located closer to the skull. However, this and other aspects of longitudinal variation in axial muscle morphology are poorly documented either within or between species of snakes. For the anterior half of the trunk in 25 phylogenetically and morphologically diverse species of snakes, we compared patterns of segmentation and morphology of the m. spinalis (SP) muscle, which is one of the largest epaxial muscles in snakes that is used in most types of locomotion and while constricting prey. Among the species studied, mid-body segments of the SP muscle spanned from 9-46 vertebrae, whereas the most anterior segments spanned from 7-17 vertebrae. In all species examined, the anterior decreases in total span of SP segments resulted primarily from reduced length of the long anterior anterior tendon rather than contractile tissue. Furthermore, reductions in segmental length occurred at more posterior locations than were necessary based on lengths of the mid-body segments. Several modifications in SP segments were observed that resulted in reduced total span, some of which varied among taxa. The number of vertebrae anterior to the origin of the most anterior SP segment attachment was fairly uniform among snakes (usually 5-8) and may facilitate identifying a posterior boundary for a cervical region in snakes.

Committee:

Bruce Jayne, PhD (Committee Chair); Daniel Buchholz, PhD (Committee Member); Elke Buschbeck, PhD (Committee Member)

Subjects:

Biology

Keywords:

Segmentation; Longitudinal Variation; Snakes; Serial Homologues;

Amrhein, Kelly EAn analysis of outcomes in maltreated youth: The transmission of neighborhood risk through caregiver aggression and depression
Doctor of Philosophy (Ph.D.), Bowling Green State University, 2016, Psychology/Clinical
Resilience to childhood maltreatment, or the ability of children to make a "good" adjustment despite the odds (Kerig, Ludlow, & Wenar, 2012), has gained widespread attention in the child maltreatment literature. Although individual child and caregiver factors that contribute to the development of resilience have been thoroughly examined, other factors have received less attention in the resilience literature, such as the neighborhood in which the maltreated child resides. The current study used path analysis to examine how neighborhood collective efficacy influences caregiver depression and aggression, which in turn were expected to influence the youth outcomes of internalizing, externalizing, delinquency, substance use, and education/employment over time. The overall proposed model did not provide an adequate fit for the data. However, two sub-models including aggression and depression as the sole mediators provided adequate fit, though the parameter estimates were not significant in these models. Despite this outcome, several interesting findings emerged. Neighborhood collective efficacy at age 12 was not correlated with any youth outcomes at age 18. Finally, caregiver psychological aggression, but not physical aggression, was positively associated with youth outcomes at age 18. Directions for future research and implications for policies are discussed.

Committee:

Carolyn Tompsett (Advisor); Eric Dubow (Committee Member); Marie Tisak (Committee Member); Danielle Kuhl (Other)

Subjects:

Psychology

Keywords:

childhood maltreatment; collective efficacy; aggression; depression; parents; path analysis; delinquency; substance use; externalizing; internalizing; education; employment; outcomes; longitudinal

Cutter, Matthew R.Dispersion in Steady Pipe Flow with Reynolds Number Under 10,000
MS, University of Cincinnati, 2004, Engineering : Environmental Engineering
The longitudinal dispersion coefficient of a conservative tracer (CaCl2) was calculated from continuous flow tests in a dead-end pipe system. The system consisted of 6-inch diameter PVC pipe with a test length of approximately 44 meters. Flow conditions ranged from laminar to turbulent regimes, with a Reynolds number range of 1000 to 10000. Two static mixers in series were used to homogenize the tracer concentration across the cross-section of pipe. The conductivity of the tracer was measured at two locations downstream of the injection and mixers using a conductivity probe at a point in the cross-section. Dispersion coefficients calculated by the method of moments are plotted versus Reynolds number. Test results show increasing time-averaged dispersion rate in the laminar flow regime and a portion of the transitional flow regime with increasing Reynolds number. At a flow rate corresponding to a Reynolds number (Re) of approximately Re=2400, the dispersion rate reaches a maximum value and then decreases until approximately Re=4000. As the tests enter the turbulent flow regime, the dispersion rate is minimized due to the plug-flow behavior inherent to turbulent flow. Results indicate that dispersion plays a more important role in mass transport in laminar and transitional flow than advective mass transport. Incorporating dispersion estimates into network water quality models will improve quality predictions for the dead-end portions of the network.

Committee:

Dr. Steven Buchberger (Advisor)

Subjects:

Engineering, Environmental

Keywords:

longitudinal dispersion coefficient; tracer; laminar; water distribution network; dead-end; simulator

Getzoff, Elizabeth A.Emotional Well-Being in Young Adults with Sickle Cell Disease and Matched Comparison Peers: A Longitudinal Study
PhD, University of Cincinnati, 2004, Arts and Sciences : Psychology

Sickle cell diseases (SCD) are a group of genetic conditions that primarily affect African Americans in the United States. With improved survival rates of 85% of children reaching adulthood, there has been increased concern about the quality of life for affected individuals. Research suggests that difficulties with emotional well-being (e.g., higher levels of depressive and internalizing symptoms, and more negative self-concept) may be most pronounced when disease severity is greater and may increase as youth approach adulthood and face the challenges associated with this life-transition. The current investigation evaluated whether young adults with SCD evidenced poorer emotional well-being and greater deterioration in emotional functioning over time than non-chronically ill comparison peers (COMPs). In addition, the association between disease severity and emotional well-being for young adults with SCD was also examined. Given risk to the central nervous system by SCD, exploratory analyses of cognitive functioning and consideration of whether deficits in IQ would account for functioning in this sample was examined.

Longitudinal evaluations were completed for individuals with SCD (N = 48) and COMPs (N = 49). Data were collected during home-based assessments when children were between 8-15 years of age (Time 1) and again after age 18 (Time 2). Self and parent-report measures of emotional well-being as measured by the Children’s Depression Inventory, Beck Depression Inventory, Self-Perception Profile for Children and Adolescents, and Child Behavior Checklist were obtained and disease severity was formulated based on medical chart review.

No significant group differences (SCD vs. COMP) were found for young adults on measures of self worth, depression, and internalizing behavior. The continuity of emotional well-being over time did not differ between groups. Disease severity failed to account for variance in young adult outcomes. These results suggest that young adults with SCD exhibit psychological hardiness over time.

Committee:

Dr. Kathleen Burlew (Committee Co-Chair); Kathryn Vannatta (Committee Co-Chair); Shawn Bediako (Other); Christine Hovanitz (Other); Robert Noll (Other); Scott Powers (Other)

Subjects:

Psychology, Developmental

Keywords:

Sickle Cell Disease; Emotional Well-being; Longitudinal Study; Internalizing

Nakai, YoshieResilience of Mature Job Seekers: A Four-Wave Longitudinal Investigation
Doctor of Philosophy, University of Akron, 2011, Psychology-Industrial/Gerontological
The current study investigated resilience among older job seekers in a longitudinal design. Based on resilience literature and Social Cognitive theory, effects of job search self-efficacy, expectation, and social support were examined for four different job search behaviors: contacting friends and family, contacting potential employers, using traditional methods, and using internet. In this study, a total of 376 adults above age 40 were recruited from a local job fair. Participants completed a survey at the job fair and were followed up by three phone surveys over a 3-month period. The data were analyzed using growth curve modeling. It was found that there was between-person variability in job search at initial point. As time went on job seekers were less likely to contact potential employers. There was significant variability in growth patterns for search by traditional methods such as looking in newspapers and preparing resumes. In examining the proposed resilience mechanism, the current result highlighted the criticality of job search self-efficacy over time. Those who were confident in carrying out search behavior showed more resilience to keep searching for a job. The results from the current study and implications of the findings are discussed in detail.

Committee:

Andrea F. Snell, Dr. (Advisor); Dennis Doverspike, Dr. (Committee Member); Cheryl Elman, Dr. (Committee Member); Harvey L. Sterns, Dr. (Committee Member); Linda M. Subich, Dr. (Committee Member)

Subjects:

Psychology

Keywords:

job seeking behavior; older workers; job search self-efficacy; longitudinal

Singh, Angella HarjaniFollow-Up Study Of The Effects Of A Supplemental Early Reading Intervention On The Reading Skills Of Urban At-Risk Primary Learners
Doctor of Philosophy, The Ohio State University, 2008, ED Physical Activities and Educational Services
This study represents the third year of a three-year investigation of the effects of kindergarten literacy intervention on the reading risk of urban learners. The 41 available second-grade participants included African Americans (44%), European Americans (14%), and English language learners (ELLs) (22%). All of the participants were from low socioeconomic backgrounds and qualified for free or reduced lunch. The three groups consisted of 13 students who had received one year of supplementary early literacy intervention, 14 students who had received two years of supplementary early literacy intervention, and 14 comparison students who did not receive supplementary intervention. During Year 3 none of the three groups received supplemental instruction. This year was devoted to follow-up assessments of the students' reading performance one to two years following intervention. All participants were progressively monitored on oral reading fluency and comprehension as measured by the DIBELS. Additionally, the three groups were compared pre- and posttest on the Woodcock Johnson-III and the CTOPP. Thus, the purpose of this year of follow-up was to determine the relative second-grade reading status of students relative to the amount of treatment they received. A secondary interest was to assess the relative performance of some especially high-risk subgroups such as ELLs and African American males. Data were analyzed with regression models, contrasts, growth curves, and repeated measures mixed-effects modeling. Results showed that the strong responders (One-Year ERI Treatment students) maintained gains made from the intervention and performed higher than their initially higher performing comparison peers (Comparison group) on all measures assessed. The treatment resistors (Two-Year ERI Treatment students) continued to make progress through second grade, but the gains were not large enough to close the reading gap. Many of the Comparison students, who were initially at low or no risk in kindergarten, were found to have lost ground, and were at risk for reading failure. Some of the ELLs showed similar reading performance to their Non-ELL peers and continued to maintain the reading gains made through the end of second grade. The African American males were found to be reading at approximately one grade level lower than their same age peers and the achievement gap continued to widen with time. The findings highlight the importance of early literacy intervention, progressive monitoring, and continued supplementary instruction to prevent and minimize reading risk.

Committee:

Dr. Gwendolyn Cartledge, PhD (Advisor); Ralph Gardner, III/PhD (Committee Member); Moira Konrad, PhD (Committee Member)

Subjects:

Behaviorial Sciences; Biomedical Research; Black History; Education; Educational Evaluation; Educational Psychology; Elementary Education; Psychology; Reading Instruction; Teacher Education

Keywords:

urban learners; African American males; English Language Learners; at risk; supplemental early reading interventions; secondary interventions; follow-up study; longitudinal study

CHERUVU, VINAY KUMARCONTINUOUS ANTEDEPENDENCE MODELS FOR SPARSE LONGITUDINAL DATA
Doctor of Philosophy, Case Western Reserve University, 2012, Epidemiology and Biostatistics

Antedependence (AD) models are useful for modeling nonstationary covariance structures for longitudinal data. A limitation of these models is that they are discrete; that is, they do not recognize an underlying continuous correlation structure over a time range of interest. In addition, they are problematic for sparse data, as they rely on the particular, possibly random, measurement times obtained and involve a large number of parameters when the number of unique measurement times is large. This situation creates difficulties in carrying out available numerical methods for maximum likelihood (ML) estimation. In this research, we define a continuous AD model based on a ’non-stationarity function’. We discuss the interpretation of this function and special cases. In addition, we present a novel approach to estimation for this model using nonlinear least squares. We examine properties of this method in simulation studies, and show that it does as well as ML for balanced data, but also allows valid estimation in sparse data situations where ML breaks down. We also consider the use of the continuous AD covariance structure in the general linear model and provide a generalized least squares method to estimate the mean structure. We apply the above methods to data from the Multi Center AIDS Cohort Study (MACS). Finally, we discuss implications and issues involving study design.

According to the simulation studies, The proposed new approach using nonlinear least squares (NLLS) for estimation of correlation parameters in the continuous 1st order ante-dependence model did better compared to the MLE approach in terms of bias, and MSE, for small samples. As the sample size increased both approaches were similar in terms of bias and MSE. The proposed new approach estimated the underlying non-stationary correlation structure with minimal bias in all scenarios of sparse longitudinal data, including the scenario of complete longitudinal data, across all sample sizes.

Committee:

JEFFREY ALBERT, PhD (Advisor); PAUL JONES, PhD (Committee Chair); ROBERT KALAYJIAN, MD (Committee Member); MARK SCHLUCHTER, PhD (Committee Member)

Subjects:

Biostatistics; Health Sciences; Medicine; Statistics

Keywords:

Antedependence Models; Sparse Longitudinal Data; HIV; AIDS; Nonlinear Least Squares

Stensland, Michael D.Modeling Treatment Outcome: Improving Clinical Meaning Through the Use of Nonlinear Growth Curve Models
Doctor of Philosophy (PhD), Ohio University, 2004, Psychology (Arts and Sciences)

This methods paper overviewed the challenges in statistical analyses of clinical trials with continuous scale outcomes measures. The currently used statistical methods for this type of data were identified from clinical trials published between September 16, 2001 and September 15, 2002 in three respected journals: one from psychology, psychiatry, and medicine were reported. The strengths and limitations of the commonly used statistical models were examined. To address some problems that plague commonly used statistical methods for this type of data, an intrinsically nonlinear function was developed and implemented on a clinical trial dataset using nonlinear growth curve methodology. The results of the nonlinear growth curve model were compared to those of repeated measures ANOVA, the mixed model for repeated measures, and a polynomial linear growth curve model.

For a clinical trial that evaluated outcomes from pharmacological and behavioral interventions for treating chronic tension-type headaches, the nonlinear growth curve model provided a better fit to the data based on Schwarz’s Bayesian Information Criteria and Akaike’s Information Criteria, more reasonable subject-specific and interpolated predicted values, and more clinically meaningful coefficients than the competing models. The four coefficients for the nonlinear function represented the baseline symptom level, the amount of change, and two different aspects of the rate of change. Despite the increased complexity in estimation, this nonlinear growth curve model appears to be viable alternative for analyzing clinical trial data.

Committee:

Kenneth Holroyd (Advisor)

Subjects:

Psychology, Clinical

Keywords:

Nonlinear Growth Curve; Clinical Trials; Treatment Outcome; Longitudinal Analysis; Data Analysis; Chronic Tension Headache

Tanaka, HirokiDevelopment of MOKE Spectrometer for Magneto-optical Studies of Novel Magnetic Materials and Quantum Structures
Master of Science (MS), Ohio University, 2008, Electrical Engineering (Engineering and Technology)
The progress in modern, widely-defined information technology strongly depends on the ability of precise characterization of variety of materials in the wide range of anticipated parameters. Novel magnetic materials and magnetic structures are the core of the spintronics in which a manipulation of electrons spins opens a door to new concepts of practical applications. The magneto-optic is an interesting approach to effectively assess properties of spintronic materials due to the strong interaction of photons with spins mediated through spin-orbit coupling. This is manifested by observation of Faraday, Voigt and Kerr effects in magnetic materials. These effects crucially depend on the spin-orbit interactions in the starting and/or the ending state of the optical transition considered. In this work we exclusively focused on the magneto-optical Kerr effect through the development of and testing of the automated Magneto-Optical Kerr Effect (MOKE) spectrometer operating in polar and longitudinal geometries at room temperature. The constructed MOKE system has proven to be central to perform magneto-optical and magnetic characterizations of selected test and research samples. In particular, we were able to confirm the functionality of the MOKE by measuring Kerr rotation hysteresis loops of the Pt/Co superlattice test samples. Furthermore, a set of new results was obtained for the different epitaxially grown GaN/Fe material systems. The observed Kerr rotation signal for GaN/Fe was interpreted as the clear evidence for a strong spin-orbit interaction occurring in these novel magnetic materials. In addition to the conducted experimental work, special attention was dedicated to derive an analytically comprehensive description of the Kerr rotation and Kerr ellipticity in the general case of polar and longitudinal geometries. Finally, relying on the expertise gained during the MOKE spectrometer construction and testing, we proposed to upgrade the system necessary to improve its reliability and expand the scope of available magneto-optical measurement techniques at Ohio University.

Committee:

Wojciech M. Jadwisienczak, PhD (Advisor)

Subjects:

Electrical Engineering

Keywords:

MOKE; polar; Longitudinal; Kerr rotation; Kerr ellipticity; Co; Pt;Fe; GaN; LabVIEW; Setup; calibration; Lorentz; Magneto optical Kerr effect

Panneerselvam, AshokA Joint Model of Longitudinal Data and Time to Event Data with Cured Fraction
Doctor of Philosophy, Case Western Reserve University, 2010, Epidemiology and Biostatistics
A joint model to analyze longitudinal prostate specific antigen (PSA) data and time to recurrence in prostate cancer patients after receiving radiation therapy is developed. We assume a fraction of patients to be cured, i.e., where the risk of recurrence is assumed to be zero. In the model, the probability of cure is modeled using a logistic model, and the log-transformed serial PSA measurements are modeled using a linear mixed effects model. In the uncured group the random effects of the longitudinal data and a suitable transformation of time to event is assumed to have a multivariate normal distribution. An EM algorithm is formulated to estimate the parameters of the model and the standard errors are obtained from bootstrapping and numerical methods available in SAS/IML. Estimation of parameters numerically using the Newton-Raphson method is also explored. Properties and performance of the model and estimates are examined using simulation studies. As an extension to the above model a joint model for longitudinal data and time to event data with latent subclasses is developed. The applications of these models are presented on an example dataset. The BIC criterion is used for model selection.

Committee:

Mark Schluchter, PhD (Committee Chair); Jeffrey Albert, PhD (Committee Member); Pingfu Fu, PhD (Committee Member); Michael Kattan, PhD (Committee Member)

Subjects:

Biostatistics

Keywords:

Joint Model; Longitudinal data; Time to event; Cured Fraction

Xu, ZhiguangModeling Non-Gaussian Time-correlated Data Using Nonparametric Bayesian Method
Doctor of Philosophy, The Ohio State University, 2014, Statistics
This dissertation proposes nonparametric Bayesian methods to study a large class of non-Gaussian time-correlated data, including non-Gaussian time series and non-Gaussian longitudinal datasets. When a time series is noticeably non-Gaussian, classical methods with Gaussian innovations will yield poor fits and forecasts, but the joint distribution of a non-Gaussian time series is often difficult to specify. To overcome this difficulty, we propose the copula-transformed AR (CTAR) model. This model utilizes the copula method to determine the joint distribution of the observed series by separating the marginal distribution from the serial dependence. In implementation, we model the observed series as a nonlinear, nonparametric transformation from a latent Gaussian series. The marginal distribution of the observed series follows a nonparametric Bayesian prior distribution having large support, and therefore any non-Gaussian distribution can be well approximated. The dependence structure of the observed series is characterized indirectly through the latent Gaussian time series, so that we can borrow some classic Gaussian time series modeling methods to model the serial dependence. We also extend the proposed nonparametric Bayesian copula methods to model stationary time series with changing conditional volatility by developing copula-transformed AR-GARCH (CTAR-GARCH) model, which describes the observed series as a nonlinear, nonparametric transformation from an AR-GARCH latent series. We conduct simulations and show the CTAR and CTAR-GARCH models' advantages in capturing non-Gaussian marginal and predictive distributions. We also fit the CTAR-GARCH models to stock index return series and conclude that they yield better predictions than the classical AR-GARCH models with Gaussian innovation. We further extend our models to the non-Gaussian longitudinal analysis setting. We model an observed within-subject response series as a transformation from a latent Gaussian series. The latent series specifies the within-subject dependence structure and the transformation function specifies marginal distribution of response variable. Similar to CTAR models, a marginal distribution of the response variable has a nonparametric Bayesian prior distribution and is therefore flexible in shape. We conduct simulations and study a 100km-race real dataset where the response variable is noticeably non-Gaussian. The data analysis demonstrates the advantage of copula-transformed models' performance in model fitting and prediction compared with the Gaussian-based models when the data is truly non-Gaussian and when the mean function is correctly specified. We also study the situations where the mean function shifts in the out-of-sample data. We find that the model's predictive performance for individuals is impacted by the shifts. The copula-transformed models are more sensitive to the shift than the Gaussian-based models. We also study the predictive performance of the contrasts. The models' predictive performance remains fairly robust to the shifts, and the copula-transformed models outperform the Gaussian-based models in contrast predictions. The proposed method can be extended in many directions, including using other transformation functions (e.g., a transformation using Polya tree prior).

Committee:

Steven MacEachern (Advisor); Xinyi Xu (Advisor); Mario Peruggia (Committee Member)

Subjects:

Statistics

Keywords:

time series, longitudinal data, copula, nonparametric Bayesian method

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