Matching Items (510)
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
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
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
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
Breast microcalcifications are a potential indicator of cancerous tumors. Current visualization methods are either uncomfortable or impractical. Impedance measurement studies have been performed, but not in a clinical setting due to a low sensitivity and specificity. We are hoping to overcome this challenge with the development of a highly accurate impedance probe on a biopsy needle. With this technique, microcalcifications and the surrounding tissue could be differentiated in an efficient and comfortable manner than current techniques for biopsy procedures. We have developed and tested a functioning prototype for a biopsy needle using bioimpedance sensors to detect microcalcifications in the human body. In the final prototype a waveform generator sends a sin wave at a relatively low frequency(<1KHz) into the pre-amplifier, which both stabilizes and amplifies the signal. A modified howland bridge is then used to achieve a steady AC current through the electrodes. The voltage difference across the electrodes is then used to calculate the impedance being experienced between the electrodes. In our testing, the microcalcifications we are looking for have a noticeably higher impedance than the surrounding breast tissue, this spike in impedance is used to signal the presence of the calcifications, which are then sampled for examination by radiology.
ContributorsWen, Robert Bobby (Co-author) / Grula, Adam (Co-author) / Vergara, Marvin (Co-author) / Ramkumar, Shreya (Co-author) / Kozicki, Michael (Thesis director) / Ranjani, Kumaran (Committee member) / School of Molecular Sciences (Contributor) / Electrical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Breastfeeding has been shown by a number of studies to have numerous benefits on both the mother and the infant. Major health organizations such as the World Health Organization (WHO), now agree that breastfeeding should be encouraged and supported in all countries. But like many things, the wheels of the law are slow to catch up with scientific evident. Although breastfeeding is supported, working women do not have the option of breastfeeding without consequences. For example, in 2003, Kirstie Marshall, a then member of parliament in Australia was ejected from the lower house chamber on February 23, for breastfeeding her baby [3]. According to standing order 30 at the time, "Unless by order of the House, no Member of this House shall presume to bring any stranger into any part of the House appropriated to the Members of this House while the House, or a Committee of the whole House, is sitting" [3]. The rules did not specify the age of strangers, so the then 11-day-old baby, Charlotte Louise and her mother were shown the exit door of parliament. She had to choose between being present at times of major discussions or leaving the house to breastfeed her child, she chose to leave. More recent statistics show that developed nations like the US and Australia which also have high rates of women employment had low rates of breastfeeding. This might mean that workplace policies do not favor breastfeeding or expressing milk at work. Fortunately, laws have since been introduced in both the United States and Australia that support breastfeeding at the workplace. The next step would be to access how these laws affect breastfeeding statistics and how variation between these two countries like the paid parental leave in Australia (which is not present in all US states) would affect these numbers.
ContributorsSakala, Lydia (Author) / Alison, Alison (Thesis director) / Reddy, Swapna (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Ketone bodies are produced in the liver from the acetyl CoA derived from fatty acids that cannot enter the Krebs cycle. This is a sub-analysis of a larger study which had numerous outcome markers. This analysis focuses on the relationship between ketone blood levels and cognition. The study looked at the relationship between Time Restricted Feeding (TRF), a method of intermittent fasting. TRF is something that can be easily adapted into an individual’s lifestyle and has been shown to have multiple advantages. This 8-week study began with 23 enrolled participants, but due to COVID-19 only 11 participants could be tested for cognition and blood ketone levels after week 4. All participants had similar ranges of weight, height, age, BMI, hip, and waist measurements at baseline. Moreover, these demographic variables were not related to ketone levels or cognition. The data indicate that ketone bodies increased in participants practicing TRF and that the increase in ketone bodies in the blood, specifically β-hydroxybutyrate was strongly correlated to increased cognitive function. This is consistent with theories that elevated ketone levels allowed for early hunter-gather communities and other mammals to survive prolonged periods of nutrient deprivation while keeping high cognitive function.
ContributorsTaha, Basel Mahmoud (Author) / Johnston, Carol (Thesis director) / Karen, Sweazea (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
The purpose of this thesis experiment was to design and create an Acoustically Active Cannula (AAC), which is furnished by a piezoelectric crystal placed at its tip that produces an acoustic navigation signal. I tested the functionality of the cannula in vitro and demonstrated its navigational abilities in vivo in anesthetized pigs. This experiment was based upon ultrasound science and technology, and thus some practical experience with conventional (B-mode) and Doppler ultrasound was achieved as well. The results of bench and experimental animal studies indicated proper functionality of the AAC for identification and spatial navigation of its tip with color Doppler ultrasound imaging.
ContributorsShamsa, Kayvan (Author) / Tyler, William (Thesis director) / Belohlavek, Marek (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
The academic study of eSports, or professional competition through the medium of video games, has tended to focus on players' motivations to play and watch eSports as well as marketing concerns of huge eSports corporations. Instead of utilizing marketing or psychology to analyze this phenomenon, I investigate three areas of focus in accordance with available literature: the fans and their characteristics, the design of the game itself, and the relationship between fans and the game's developer. This investigation was conducted by first examining existing literature surrounding eSports fans, then collecting public domain data such as Reddit posts, forum posts, and YouTube videos, and last by studying interviews with developers and players. With this thesis, I apply a fan studies approach to eSports by creating a series of indicators based in each of the three focus areas which can be utilized as a systematic method of evaluating an eSport's popularity and growth.
ContributorsHilliker, Noah Henry (Author) / Ingram-Waters, Mary (Thesis director) / Schmidt, Peter (Committee member) / Anderson, Sky (Committee member) / School of Molecular Sciences (Contributor) / W.P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
DescriptionThis project is designed to generate enthusiasm for science among refugee students in hopes of inspiring them to continue learning science as well as to help them with their current understanding of their school science subject matter.
ContributorsSipes, Shannon Paige (Author) / O'Flaherty, Katherine (Thesis director) / Gregg, George (Committee member) / School of Molecular Sciences (Contributor) / Division of Teacher Preparation (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12