Matching Items (619)
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
This paper will be exploring a marketing plan for a Kpop Fan artist, Jennifer Lee. Kpop is a genre of music originating from South Korea that provides a whole-package entertainment. Fan artists are producers who create produce for the consumption and purchase of other Kpop fans. The paper will consider segmentation and the products and platforms that best target them in order to maximize revenue. A survey was performed with a sample size of 314 participants to find out consumer behavior and preference as well as producer situation. Consumers come from both the United States and abroad. Customers come directly and almost exclusively from followers. Therefore, increasing the number of followers on Instagram is essential to increasing revenue. Jennifer has time, resource, and ability constraints, while the market has limited potential. The conclusion is that Jennifer should become more organized as a business. To grow her following, she should cater more towards the most popular fandoms (BTS), make art tutorials, consider collaborations, and better inform followers of her products/services available for purchase. The social media platforms key to marketing Jennifer's products are Instagram and Twitter. Other platforms to be used to increase exposure are Tumblr, Amino Apps, DeviantArt, Reddit, and YouTube. She must also declutter all of these virtual storefronts of unnecessary content to varying degrees in order to build ease of access and a trustworthy brand image. The best platforms for transaction is a personal store, RedBubble (a website that allows users to sell a variety of products with their uploaded images printed onto them), Patreon, and in-person at conventions.
ContributorsXu, Everest Christine (Author) / Eaton, Kathryn (Thesis director) / Ingram-Waters, Mary (Committee member) / Department of Marketing (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
The advertising agency, in its variety of forms, is one of the most powerful forces in the modern world. Its products are seen globally through various multimedia outlets and they strongly impact culture and economy. Since its conception in 1843 by Volney Palmer, the advertising agency has evolved into the recognizable—and unrecognizable—firms scattered around the world today. In the United States alone, there are roughly 13.4 thousand agencies, many of which also have branches in other countries. The evolution of the modern advertising agency coincided with, and even preceded, some of the major inflection points in history. Understanding how and why changes in advertising agencies affected these inflection points provides a glimpse of understanding into the relationship between advertising, business, and societal values.
In the pages ahead we will explore the future of the advertising industry. We will analyze our research to uncover the underlying trends pointing towards what is to come and work to apply those explanations to our understanding of advertising in the future.
In the pages ahead we will explore the future of the advertising industry. We will analyze our research to uncover the underlying trends pointing towards what is to come and work to apply those explanations to our understanding of advertising in the future.
ContributorsHarris, Chase (Co-author) / Potthoff, Zachary (Co-author) / Gray, Nancy (Thesis director) / Samper, Adriana (Committee member) / Department of Information Systems (Contributor) / Department of Marketing (Contributor) / Herberger Institute for Design and the Arts (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
The goal of our project was to determine how to create the most marketable hockey team. To do this, consumer needs, team psychology, and financing were all researched and evaluated. With this information, a business plan was designed around the next NHL expansion team. Two surveys, one for marketing distributed to the general public, and one for team psychology distributed to current and former hockey players were created and sent out, while data for the financing aspect was collected by comparing data from other NHL teams and franchises from different sports. In terms of financials, this comes in lower than average ticket prices, a nice and expensive stadium, the ideal city to generate capital, and sufficient money spent on advertising. Our ticket prices of $140 is based on having a low enough price to generate lots of demand while high enough to make a profit. The $600 million stadium (which will be fully funded) will surely draw a significant crowd. Choosing Seattle as a city is the most ideal to meet these goals and lastly, in meeting with an NHL GM, we determined $4 million in yearly advertising costs as sufficient in creating the most marketable team. Throughout this whole process, we remained data focus. We focused on data from a customized marketing survey, organizational structures, salary cap, and attendance. What our marketing survey results showed us is that our potential fans wanted three characteristics in a hockey team: speed, intensity, and scoring. In looking at organizational structures teams that exemplified these characteristics had a heavy emphasis on development and scouting. So we built our organizational tree around those two ideals. We hired GM Mike Futa, a current director of player personnel for the L.A. Kings, and Head Coach Adam Oates, a current skills development coach for top players to bring those ideals to fruition. In constructing our team we replicated the rules set forth for the Vegas Knights' expansion draft and hypothesized a likely protected list based off of last years lists. As a result we were able to construct a team that statistically out performed the Vegas Knights draft numbers by double, in goals, assists, and points, while also beating them in PIM. Based off of these numbers and an analysis of how goals translate into game attendance we are confident that we have constructed a team that has the highest potential for marketability. For the team psychology area, when creating a roster and scouting players, some of our main findings were that it is important to pursue players who get along well with their teammates and coaching staff, are aggressive, are leaders on the team, and are vocal players who communicate effectively. We also recommended avoiding players who significantly portrayed any "pet-peeve" traits, with the most emphasis placed on "disrespectful toward teammates," and the least emphasis placed on "over-aggression." By following all of these recommendations, we believe the most marketable hockey team possible can be created.
ContributorsQuinn, Colin Christopher (Co-author) / Spigel, Carlos (Co-author) / Meyer, Matt (Co-author) / Eaton, John (Thesis director) / McIntosh, Daniel (Committee member) / Department of Marketing (Contributor) / Sandra Day O'Connor College of Law (Contributor) / Department of Management and Entrepreneurship (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
In recent years, companies have been expanding their business efforts on a global scale. This project explores this expansion of American-based multinational corporations (MNCs) in Ireland, and the comparison of how their culture motivation in the workplace. We did a cultural study using Hofstede and Trompenaars' cultural dimensions of the two countries then used McClelland's Needs Theory, Equity Theory, and Herzberg's Motivation-Hygiene Theory in order to create three research questions. (1) How does the manager define success for the firm as a whole and for their employees, (2) How is the definition of success reflected in the company's corporate culture (i.e. values, norms and practices), along with how cultural values, norms and practices affect the company, and (3) How do external forces (i.e. governmental factors, workplace technology, etc.) affect the workplace environment and motivation for employees? With these we hypothesized that for research question 1, we hypothesized that from our study of Hofstede's and Trompenaars' cultural frameworks, Irish employees will show a greater tendency to favor affiliation, nAff, as opposed to a need for achievement, nAch, in American employees, according to McClelland's Needs Theory. For research question 2, we predicted that motivation would be administered through style of feedback to employees and office norms, such as autonomy, flexible hours, and work-life balance. For research question 3, we hypothesized that Ireland would have an impact from external factors such as government and technology, whereas the U.S. employees would face no clear impact. We conducted eight, qualitative interviews using a questionnaire, either in person or via video conference. The interviewees were all managers in some facet and have all had some international experience. Through the analysis of the interviews, we found that the Irish employees focused on how employees are able to help or contribute to a group (nAff), instead of looking at how the contribution of a group can be used to meet individual goals (nAch). The American companies reflected Trompenaars' definition of individualism in which employees focus on collaborating in teams, as long as individual goals are met, and benchmarked collaboration as a performance measure, tying in the need for achievement, for research question one. For the second research question, we found that employees in Ireland had a focus on teamwork in the workplace and much higher respect for work-life balance. American firms, in contrast, had a greater focus on making sure employees were contributing, meeting their goals, and getting their work done. While American firms did acknowledge work-life balance and its importance, there was a priority for coming in early and/or staying late to make sure a job got done. Findings for our third question showed that government factors did impact Ireland more, due to labor laws such as required vacation days in Ireland, and that technology had less of an impact than expected, for both countries. More importantly was our finding that the companies in Ireland were greatly impacted by the decisions made by the business executives in the United States.
ContributorsSong, Jenny Jungwon (Co-author) / Brown, William (Co-author) / Arrfelt, Mathias (Thesis director) / Moore, James (Committee member) / Department of Marketing (Contributor) / Department of Management and Entrepreneurship (Contributor) / W.P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
This paper looks at the growth of influencer marketing in application and how it has shifted the relationship between brands and consumers. Barriers to enter the space and methods of practice are discussed and analyzed to project the accessibility of obtaining influencer status. Best practices for brands and influencers are outlined based on research, and key findings are analyzed from interviewed participants that play an active role in the field. Another component of the paper includes the discussion of the significance of platform dependence regarding influencers and brands using social media channels to reach consumers. The dynamic of the relationship that exists between consumers, brands and platforms is demonstrated through a model to demonstrate the interdependence of the relationship. The final component of the paper involves the exploration of the field as an active participant through an experiment that was conducted by the researcher on behalf of the question: can anyone be an influencer? The answer to this question is explored through personal accounts on the journey during an eight month process of testing content creation and promotion to build awareness and increase engagement. The barriers to enter the space as an influencer and to collaborate with brands is addressed through the process of testing tactics and strategies on social channels, along with travel expeditions across Arizona to contribute to content creation purposed into blog articles. The findings throughout the paper are conclusive that the value of influencer marketing is increasing as more brands validate and utilize this method in their marketing efforts.
ContributorsDavis, Natalie Marie (Author) / Giles, Bret (Thesis director) / Schlacter, John (Committee member) / Department of Information Systems (Contributor) / Department of Marketing (Contributor) / Walter Cronkite School of Journalism and Mass Communication (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
While developing and maintaining a connection between a brand and a customer has always been in the forefront of marketers' agendas, it has become an even more pressing goal as digital trends in marketing surface. Although the idea of using rewards to foster consumer-brand connection has been around for decades, marketers are still struggling to optimize the benefits. How can marketers use rewards to better connect with their customers? Are there certain types of rewards that are more effective than others? Are certain rewards more effective when being implemented under brands of a certain personality type? In a society that values connection and relationship, marketers cannot lose their ability to appreciate customers under digital constraints and to marketplace competition. Through a field study and scenario-based experiment, we explore how and why low conditional vs. high conditional rewards influence consumer-brand connection and the role brand personality plays.
ContributorsBauer, Madelaine Anne (Co-author) / Bryant, Kelly (Co-author) / Lisjak, Monika (Thesis director) / Samper, Adriana (Committee member) / Department of Finance (Contributor) / W.P. Carey School of Business (Contributor) / Department of Marketing (Contributor) / Sandra Day O'Connor College of Law (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05