Matching Items (901)
Description
Many longitudinal studies, especially in clinical trials, suffer from missing data issues. Most estimation procedures assume that the missing values are ignorable or missing at random (MAR). However, this assumption leads to unrealistic simplification and is implausible for many cases. For example, an investigator is examining the effect of treatment on depression. Subjects are scheduled with doctors on a regular basis and asked questions about recent emotional situations. Patients who are experiencing severe depression are more likely to miss an appointment and leave the data missing for that particular visit. Data that are not missing at random may produce bias in results if the missing mechanism is not taken into account. In other words, the missing mechanism is related to the unobserved responses. Data are said to be non-ignorable missing if the probabilities of missingness depend on quantities that might not be included in the model. Classical pattern-mixture models for non-ignorable missing values are widely used for longitudinal data analysis because they do not require explicit specification of the missing mechanism, with the data stratified according to a variety of missing patterns and a model specified for each stratum. However, this usually results in under-identifiability, because of the need to estimate many stratum-specific parameters even though the eventual interest is usually on the marginal parameters. Pattern mixture models have the drawback that a large sample is usually required. In this thesis, two studies are presented. The first study is motivated by an open problem from pattern mixture models. Simulation studies from this part show that information in the missing data indicators can be well summarized by a simple continuous latent structure, indicating that a large number of missing data patterns may be accounted by a simple latent factor. Simulation findings that are obtained in the first study lead to a novel model, a continuous latent factor model (CLFM). The second study develops CLFM which is utilized for modeling the joint distribution of missing values and longitudinal outcomes. The proposed CLFM model is feasible even for small sample size applications. The detailed estimation theory, including estimating techniques from both frequentist and Bayesian perspectives is presented. Model performance and evaluation are studied through designed simulations and three applications. Simulation and application settings change from correctly-specified missing data mechanism to mis-specified mechanism and include different sample sizes from longitudinal studies. Among three applications, an AIDS study includes non-ignorable missing values; the Peabody Picture Vocabulary Test data have no indication on missing data mechanism and it will be applied to a sensitivity analysis; the Growth of Language and Early Literacy Skills in Preschoolers with Developmental Speech and Language Impairment study, however, has full complete data and will be used to conduct a robust analysis. The CLFM model is shown to provide more precise estimators, specifically on intercept and slope related parameters, compared with Roy's latent class model and the classic linear mixed model. This advantage will be more obvious when a small sample size is the case, where Roy's model experiences challenges on estimation convergence. The proposed CLFM model is also robust when missing data are ignorable as demonstrated through a study on Growth of Language and Early Literacy Skills in Preschoolers.
ContributorsZhang, Jun (Author) / Reiser, Mark R. (Thesis advisor) / Barber, Jarrett (Thesis advisor) / Kao, Ming-Hung (Committee member) / Wilson, Jeffrey (Committee member) / St Louis, Robert D. (Committee member) / Arizona State University (Publisher)
Created2013
Description
A noninvasive optical method is developed to monitor rapid changes in blood glucose levels in diabetic patients. The system depends on an optical cell built with a LED that emits light of wavelength 535nm that is a peak absorbance of hemoglobin. As the glucose concentration in the blood decreases, its osmolarity also decreases and the RBCs swell and decrease the path length absorption coefficient. Decreasing absorption coefficient increases the transmission of light through the whole blood. The system was tested with a constructed optical cell that held whole blood in a capillary tube. As expected the light transmitted to the photodiode increases with decreasing glucose concentration. The average response time of the system was between 30-40 seconds. The changes in size of the RBC cells in response to glucose concentration changes were confirmed using a cell counter and also visually under microscope. This method does not allow measuring the glucose concentration with an absolute concentration calibration. It is directed towards development of a device to monitor the changes in glucose concentration as an aid to diabetic management. This method might be improvised for precision and resolution and be developed as a ring or an earring that patients can wear.
ContributorsRajan, Shiny Amala Priya (Author) / Towe, Bruce (Thesis advisor) / Muthuswamy, Jitendran (Committee member) / LaBelle, Jeffrey (Committee member) / Arizona State University (Publisher)
Created2013
Description
Cellular heterogeneity is a key factor in various cellular processes as well as in disease development, especially associated with immune response and cancer progression. Cell-to-cell variability is considered to be one of the major obstacles in early detection and successful treatment of cancer. Most present technologies are based on bulk cell analysis, which results in averaging out the results acquired from a group of cells and hence missing important information about individual cells and their behavior. Understanding the cellular behavior at the single-cell level can help in obtaining a complete profile of the cell and to get a more in-depth knowledge of cellular processes. For example, measuring transmembrane fluxes oxygen can provide a direct readout of the cell metabolism.
The goal of this thesis is to design, optimize and implement a device that can measure the oxygen consumption rate (OCR) of live single cells. A microfluidic device has been designed with the ability to rapidly seal and unseal microchambers containing individual cells and an extracellular optical oxygen sensor for measuring the OCR of live single cells. The device consists of two parts, one with the sensor in microwells (top half) and the other with channels and cells trapped in Pachinko-type micro-traps (bottom half). When the two parts of the device are placed together the wells enclose each cell. Oil is flown in through the channels of the device to produce isolated and sealed microchamber around each cell. Different fluids can be flowed in and out of the device, alternating with oil, to rapidly switch between sealed and unsealed microenvironment around each cell. A fluorescent ratiometric dual pH and oxygen sensor is placed in each well. The thesis focuses on measuring changes in the oxygen consumption rate of each cell within a well. Live and dead cells are identified using a fluorescent live/dead cell assay. Finally, the technology is designed to be scalable for high-throughput applications by controlling the flow rate of the system and increasing the cell array density.
The goal of this thesis is to design, optimize and implement a device that can measure the oxygen consumption rate (OCR) of live single cells. A microfluidic device has been designed with the ability to rapidly seal and unseal microchambers containing individual cells and an extracellular optical oxygen sensor for measuring the OCR of live single cells. The device consists of two parts, one with the sensor in microwells (top half) and the other with channels and cells trapped in Pachinko-type micro-traps (bottom half). When the two parts of the device are placed together the wells enclose each cell. Oil is flown in through the channels of the device to produce isolated and sealed microchamber around each cell. Different fluids can be flowed in and out of the device, alternating with oil, to rapidly switch between sealed and unsealed microenvironment around each cell. A fluorescent ratiometric dual pH and oxygen sensor is placed in each well. The thesis focuses on measuring changes in the oxygen consumption rate of each cell within a well. Live and dead cells are identified using a fluorescent live/dead cell assay. Finally, the technology is designed to be scalable for high-throughput applications by controlling the flow rate of the system and increasing the cell array density.
ContributorsRodrigues, Meryl (Author) / Meldrum, Deirdre (Thesis advisor) / Kelbauskas, Laimonas (Committee member) / LaBelle, Jeffrey (Committee member) / Arizona State University (Publisher)
Created2014
Description
It is common in the analysis of data to provide a goodness-of-fit test to assess the performance of a model. In the analysis of contingency tables, goodness-of-fit statistics are frequently employed when modeling social science, educational or psychological data where the interest is often directed at investigating the association among multi-categorical variables. Pearson's chi-squared statistic is well-known in goodness-of-fit testing, but it is sometimes considered to produce an omnibus test as it gives little guidance to the source of poor fit once the null hypothesis is rejected. However, its components can provide powerful directional tests. In this dissertation, orthogonal components are used to develop goodness-of-fit tests for models fit to the counts obtained from the cross-classification of multi-category dependent variables. Ordinal categories are assumed. Orthogonal components defined on marginals are obtained when analyzing multi-dimensional contingency tables through the use of the QR decomposition. A subset of these orthogonal components can be used to construct limited-information tests that allow one to identify the source of lack-of-fit and provide an increase in power compared to Pearson's test. These tests can address the adverse effects presented when data are sparse. The tests rely on the set of first- and second-order marginals jointly, the set of second-order marginals only, and the random forest method, a popular algorithm for modeling large complex data sets. The performance of these tests is compared to the likelihood ratio test as well as to tests based on orthogonal polynomial components. The derived goodness-of-fit tests are evaluated with studies for detecting two- and three-way associations that are not accounted for by a categorical variable factor model with a single latent variable. In addition the tests are used to investigate the case when the model misspecification involves parameter constraints for large and sparse contingency tables. The methodology proposed here is applied to data from the 38th round of the State Survey conducted by the Institute for Public Policy and Michigan State University Social Research (2005) . The results illustrate the use of the proposed techniques in the context of a sparse data set.
ContributorsMilovanovic, Jelena (Author) / Young, Dennis (Thesis advisor) / Reiser, Mark R. (Thesis advisor) / Wilson, Jeffrey (Committee member) / Eubank, Randall (Committee member) / Yang, Yan (Committee member) / Arizona State University (Publisher)
Created2011
Description
In the search for chemical biosensors designed for patient-based physiological applications, non-invasive diagnostic approaches continue to have value. The work described in this thesis builds upon previous breath analysis studies. In particular, it seeks to assess the adsorptive mechanisms active in both acetone and ethanol biosensors designed for breath analysis. The thermoelectric biosensors under investigation were constructed using a thermopile for transduction and four different materials for biorecognition. The analytes, acetone and ethanol, were evaluated under dry-air and humidified-air conditions. The biosensor response to acetone concentration was found to be both repeatable and linear, while the sensor response to ethanol presence was also found to be repeatable. The different biorecognition materials produced discernible thermoelectric responses that were characteristic for each analyte. The sensor output data is presented in this report. Additionally, the results were evaluated against a mathematical model for further analysis. Ultimately, a thermoelectric biosensor based upon adsorption chemistry was developed and characterized. Additional work is needed to characterize the physicochemical action mechanism.
ContributorsWilson, Kimberly (Author) / Guilbeau, Eric (Thesis advisor) / Pizziconi, Vincent (Thesis advisor) / LaBelle, Jeffrey (Committee member) / Arizona State University (Publisher)
Created2011
Description
Designing a hazard intelligence platform enables public agencies to organize diversity and manage complexity in collaborative partnerships. To maintain the integrity of the platform while preserving the prosocial ethos, understanding the dynamics of “non-regulatory supplements” to central governance is crucial. In conceptualization, social responsiveness is shaped by communicative actions, in which coordination is attained through negotiated agreements by way of the evaluation of validity claims. The dynamic processes involve information processing and knowledge sharing. The access and the use of collaborative intelligence can be examined by notions of traceability and intelligence cohort. Empirical evidence indicates that social traceability is statistical significant and positively associated with the improvement of collaborative performance. Moreover, social traceability positively contributes to the efficacy of technical traceability, but not vice versa. Furthermore, technical traceability significantly contributes to both moderate and high performance improvement; while social traceability is only significant for moderate performance improvement. Therefore, the social effect is limited and contingent. The results further suggest strategic considerations. Social significance: social traceability is the fundamental consideration to high cohort performance. Cocktail therapy: high cohort performance involves an integrative strategy with high social traceability and high technical traceability. Servant leadership: public agencies should exercise limited authority and perform a supporting role in the provision of appropriate technical traceability, while actively promoting social traceability in the system.
ContributorsWang, Chao-shih (Author) / Van Fleet, David (Thesis advisor) / Grebitus, Carola (Committee member) / Wilson, Jeffrey (Committee member) / Shultz, Clifford (Committee member) / Arizona State University (Publisher)
Created2015
Description
Olecranon fractures account for approximately 10% of upper extremity fractures and 95% of them require surgical fixation. Most of the clinical, retrospective and biomechanical studies have supported plate fixation over other surgical fixation techniques since plates have demonstrated low incidence of reoperation, high fixation stability and resumption of activities of daily living (ADL) earlier. Thus far, biomechanical studies have been helpful in evaluating and comparing different plate fixation constructs based on fracture stability. However, they have not provided information that can be used to design rehabilitation protocols such as information that relates load at the hand with tendon tension or load at the interface between the plate and the bone. The set-ups used in biomechanical studies have included simple mechanical testing machines that either measured construct stiffness by cyclic loading the specimens or construct strength by performing ramp load until failure. Some biomechanical studies attempted to simulate tendon tension but the in-vivo tension applied to the tendon remains unknown. In this study, a novel procedure to test the olecranon fracture fixation using modern olecranon plates was developed to improve the biomechanical understanding of failures and to help determine the weights that can be safely lifted and the range of motion (ROM) that should be performed during rehabilitation procedures.
Design objectives were defined based on surgeon's feedback and analysis of unmet needs in the area of biomechanical testing. Four pilot cadaveric specimens were prepared to run on an upper extremity feedback controller and the set-up was validated based on the design objectives. Cadaveric specimen preparation included a series of steps such as dissection, suturing and potting that were standardized and improved iteratively after pilot testing. Additionally, a fracture and plating protocol was developed and fixture lengths were standardized based on anthropometric data. Results from the early pilot studies indicated shortcomings in the design, which was then iteratively refined for the subsequent studies. The final pilot study demonstrated that all of the design objectives were met. This system is planned for use in future studies that will assess olecranon fracture fixation and that will investigate the safety of rehabilitation protocols.
Design objectives were defined based on surgeon's feedback and analysis of unmet needs in the area of biomechanical testing. Four pilot cadaveric specimens were prepared to run on an upper extremity feedback controller and the set-up was validated based on the design objectives. Cadaveric specimen preparation included a series of steps such as dissection, suturing and potting that were standardized and improved iteratively after pilot testing. Additionally, a fracture and plating protocol was developed and fixture lengths were standardized based on anthropometric data. Results from the early pilot studies indicated shortcomings in the design, which was then iteratively refined for the subsequent studies. The final pilot study demonstrated that all of the design objectives were met. This system is planned for use in future studies that will assess olecranon fracture fixation and that will investigate the safety of rehabilitation protocols.
ContributorsJain, Saaransh (Author) / Abbas, James (Thesis advisor) / LaBelle, Jeffrey (Thesis advisor) / Jacofsky, Marc (Committee member) / Arizona State University (Publisher)
Created2015
Description
The Pearson and likelihood ratio statistics are well-known in goodness-of-fit testing and are commonly used for models applied to multinomial count data. When data are from a table formed by the cross-classification of a large number of variables, these goodness-of-fit statistics may have lower power and inaccurate Type I error rate due to sparseness. Pearson's statistic can be decomposed into orthogonal components associated with the marginal distributions of observed variables, and an omnibus fit statistic can be obtained as a sum of these components. When the statistic is a sum of components for lower-order marginals, it has good performance for Type I error rate and statistical power even when applied to a sparse table. In this dissertation, goodness-of-fit statistics using orthogonal components based on second- third- and fourth-order marginals were examined. If lack-of-fit is present in higher-order marginals, then a test that incorporates the higher-order marginals may have a higher power than a test that incorporates only first- and/or second-order marginals. To this end, two new statistics based on the orthogonal components of Pearson's chi-square that incorporate third- and fourth-order marginals were developed, and the Type I error, empirical power, and asymptotic power under different sparseness conditions were investigated. Individual orthogonal components as test statistics to identify lack-of-fit were also studied. The performance of individual orthogonal components to other popular lack-of-fit statistics were also compared. When the number of manifest variables becomes larger than 20, most of the statistics based on marginal distributions have limitations in terms of computer resources and CPU time. Under this problem, when the number manifest variables is larger than or equal to 20, the performance of a bootstrap based method to obtain p-values for Pearson-Fisher statistic, fit to confirmatory dichotomous variable factor analysis model, and the performance of Tollenaar and Mooijaart (2003) statistic were investigated.
ContributorsDassanayake, Mudiyanselage Maduranga Kasun (Author) / Reiser, Mark R. (Thesis advisor) / Kao, Ming-Hung (Committee member) / Wilson, Jeffrey (Committee member) / St. Louis, Robert (Committee member) / Kamarianakis, Ioannis (Committee member) / Arizona State University (Publisher)
Created2018
Description
This study asks the question: does gender-based discrimination exists within Arizona State University's Army Reserve Officer Training Corps (ROTC), and if so, what are the effects of such discrimination? Within this study, discrimination is defined as: the treatment or consideration of, or making a distinction in favor of or against, a person or thing based on the group, class, or category to which that person or thing belongs, rather than on individual merit. The researcher predicted that this study would show that gender-based discrimination operates within the masculine military culture of Army ROTC at ASU, resulting from women's hyper-visibility and evidenced by their lack of positive recognition and disbelief in having a voice in the program. These expectations were based on background research claiming that the token status of women in military roles causes them to be more heavily scrutinized, and they consequentially try to attain success by adapting to the masculine military culture by which they are constantly measured. For the purposes of this study, success is defined as: the attainment of wealth, favor, or eminence . This study relies on exploratory interviews and an online survey conducted with male and female Army ROTC cadets of all grade levels at Arizona State University. The interviews and survey collected demographic information and perspectives on individual experiences to establish an understanding of privilege and marginalization within the program. These results do support the prediction that women in Army ROTC at ASU face discrimination based on their unique visibility and lack of positive recognition and voice in the program. Likewise, the survey results indicate that race also has a significant impact on one's experience in Army ROTC, which is discussed later in this study in regard to needs for future research. ASU Army ROTC includes approximately 100 cadets, and approximately 30-40 of those cadets participated in this study. Additionally, the University of Arizona and the Northern Arizona University Army ROTC programs were invited to participate in this study and declined to do so, which would have offered a greater sample population. Nonetheless, the results of this research will be useful for analysis and further discussion of gender-equality in Army ROTC at Arizona State University.
ContributorsAllemang, Lindsey Ann (Author) / Wood, Reed (Thesis director) / Switzer, Heather (Committee member) / School of Politics and Global Studies (Contributor) / School of Social Transformation (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Genocide studies have traditionally focused on the perpetrator’s intent to eradicate a particular identity-based group, using the Holocaust as their model and point of comparison. Although some aspects of the Holocaust were undoubtedly unique, recent scholars have sought to challenge the notion that it was a singular phenomenon. Instead, they draw attention to a recurring pattern of genocidal events throughout history by shifting the focus from intent to structure. One particular branch of scholars seeks to connect the ideology and tactics of imperialism with certain genocidal events. These anti-imperialist genocide scholars concede that their model cannot account for all genocides, but still claim that it creates meaningful connections between genocides committed by Western colonialist powers and those that have occurred in a neoimperialist world order shaped according to Western interests. The latter includes genocides in postcolonial states, which these scholars believe were shaped by the scars of their colonial past, as well as genocides in which imperial hegemons assisted local perpetrators. Imperialist and former colonial powers have contributed meaningfully to all of these kinds of genocides, yet their contributions have largely been ignored due to their own influence on the creation of the current international order. Incorporating the anti-imperialist perspective into the core doctrine of genocide studies may lead to breakthroughs in areas of related policy and practice, such as prevention and accountability.
ContributorsParker, Ashleigh Mae (Author) / Thies, Cameron (Thesis director) / Sivak, Henry (Committee member) / School of Politics and Global Studies (Contributor) / School of Social Transformation (Contributor) / Department of English (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05