In today's era of large-scale data, academic institutions, businesses, and government agencies are increasingly faced with heterogeneous datasets. Consequently, there is a growing need to develop effective methods for extracting meaningful insights from this type of data. Quantile, expectile, and expected shortfall regression methods offer useful…

We study flexible Bayesian methods that are amenable to a wide range of learning problems involving complex high dimensional data structures, with minimal tuning. We consider parametric and semiparametric Bayesian models, that are applicable to both static and dynamic data, arising from a multitude of areas such as economics, finance and…

Functional Data Analysis (FDA) has attracted substantial attention for the last two decades. Within FDA, classifying curves into two or more categories is consistently of interest to scientists, but multi-class prediction within FDA is challenged in that most classification tools have been limited to binary response applications. The functional…

In the 21st century, attainment of a college degree is more important than ever to achieve economic self-sufficiency, employment, and an adequate standard of living. Projections suggest that by 2020, 65% of jobs available in the U.S. will require postsecondary education. This reality creates an unprecedented demand for higher education, and…

With the development of PC, internet as well as mobile devices, we are facing a data exploding era. On one hand, more and more features can be collected to describe the data, making the size of the data descriptor larger and larger. On the other hand, the number of data itself explodes and can be collected from multiple resources. When the data…

TIMSS and PIRLS assess representative samples of students at regular intervals, measuring trends in student achievement and student contexts for learning. Because individual students are not tracked over time, analysis of international large-scale assessment data is usually conducted cross-sectionally. Gustafsson (2007) proposed examining the data…

Policymakers and professional educators attempt to be good stewards of public funds while simultaneously raising expectations for student outcomes that reflect academic excellence in the public school system. The purpose of this study was to determine the efficiency of Texas public school districts and the factors influencing the inefficiency of…

The Baccalaureate Nursing program in San Antonio, Texas experienced a decrease in National Council Licensure Examination for Registered Nurses (NCLEX-RN) on the first attempt for students graduating between 2009 and 2014 without a clear explanation for the decline. The purpose of this quantitative non-experimental correlational study was to…

Data mining is concerned with detecting patterns of data in raw datasets, which are then used to unearth knowledge that might not have been discovered using conventional querying or statistical methods. This discovered knowledge has been used to empower decision makers in countless applications spanning across many multi-disciplinary areas…

The goal of the dissertation study was to evaluate the existing DG scheduling algorithm. The evaluation was developed through previously explored simulated analyses of DGs performed by researchers in the field of DG scheduling optimization and to improve the current RT framework of the DG at TTU. The author analyzed the RT of an actual DG, thereby…

The purpose of the present quantitative correlational study was to examine if a relationship existed between the RBD phenomenon and cultural, economic, or political factors of the native countries of South Asian IT professionals living in the United States. The study on reverse brain drain was conducted to explore a growing phenomenon in the…

Response to intervention (RTI) is increasingly being used in educational settings to make high-stakes, special education decisions. Because of this, the accurate use and analysis of single-case designs to monitor intervention effectiveness has become important to the RTI process. Effect size methods for single-case designs provide a useful way to…

Establishing institutional effectiveness has beleaguered U.S. higher education institutions for thirty years. One key element of institutional effectiveness is the ability of an organization to use data for effective decision-making. This study provides new insight into this critical component of institutional effectiveness by examining the…

Using theoretical constructs of the human capital theory (Schultz, 1959) and the resource-based view of the firm (Barney, 1991), this study examines whether the type of education completed has an impact on an individual's choice between self-employment and employment with a firm. In addition, this study seeks to understand the geographic…

Economic and fiscal challenges, increased public scrutiny, and calls for accountability from stakeholders necessitate that community colleges work diligently to improve student success outcomes. Programs, services, and initiatives need to be developed and implemented that will increase student retention. Orientation is an important intervention…