Categorical data become increasingly ubiquitous in the modern big data era. In this dissertation, we propose novel statistical learning and inference methods for large-scale categorical data, focusing on latent variable models and their applications to psychometrics. In psychometric assessments, the subjects' underlying aptitude often cannot be…

The development in information science has enabled an explosive growth of data, which attracts more and more researchers to engage in the field of big data analytics. Noticeably, in many real-world applications, large amounts of data are imbalanced data since the events of interests occur infrequently. Classification of imbalanced data is an…

Models, created using different modeling techniques, usually serve different purposes and provide unique insights. While each modeling technique might be capable of answering specific questions, complex problems require multiple models interoperating to complement/supplement each other; we call this Multi-Modeling. To address the syntactic and…

In the modern world information has become the new power. An increasing amount of efforts are being made to gather data, resources being allocated, time being invested and tools being developed. Data collection is no longer a myth; however, it remains a great challenge to create value out of the enormous data that is being collected. Data modeling…

Many methods exist for imputing missing data but fewer methods have been proposed to test the missing data mechanism. Little (1988) introduced a multivariate chi-square test for the missing completely at random data mechanism (MCAR) that compares observed means for each pattern with expectation-maximization (EM) estimated means. As an alternative,…

Scientific discoveries take place within scientific communities that are established in legitimating organizations such as universities and research institutes. Often times, scientists undergo tensions and paradoxes as they evaluate the risks they are willing to accept in their work. The types of risk/benefit decisions scientists make to determine…

This dissertation develops a deeper understanding of the epistemic values of scientists, specifically exploring the proposed values of community, collaboration, connectivity and credit as part of the scholarly communication system. These values are the essence of scientists actively engaged in conducting science and in communicating their work to…

One of the objectives of any government is the establishment of an effective solution to significantly control crime. Identity fraud in Nigeria has generated global attention and negative publicity toward its citizens. The research problem addressed in this study was the lack of understanding of the dynamics that influenced the adoption and…