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Yumin Zhang – ProQuest LLC, 2022
This dissertation address two significant challenges in the causal inference workflow for Big Observational Data. The first is designing Big Observational Data with high-dimensional and heterogeneous covariates. The second is performing uncertainty quantification for estimates of causal estimands that are obtained from the application of black box…
Descriptors: Computation, Observation, Data, Public Colleges
Hyunsuk Han – ProQuest LLC, 2018
In Huggins-Manley & Han (2017), it was shown that WLSMV global model fit indices used in structural equating modeling practice are sensitive to person parameter estimate RMSE and item difficulty parameter estimate RMSE that results from local dependence in 2-PL IRT models, particularly when conditioning on number of test items and sample size.…
Descriptors: Models, Statistical Analysis, Item Response Theory, Evaluation Methods
Monea, Alexander Paul – ProQuest LLC, 2016
This project looks to fill a critical gap in our knowledge of the emergence of new forms of power, knowledge, and subjectivation that emerged during the industrial period in the United States and that continue to operate today. This critical hole is the role of what we will term "numerical mediation," which is the means by which the…
Descriptors: Computation, Power Structure, Technological Advancement, Data Analysis
Bonomi, Luca – ProQuest LLC, 2015
The Big Data phenomenon is posing new challenges in our modern society. In addition to requiring information systems to effectively manage high-dimensional and complex data, the privacy and social implications associated with the data collection, data analytics, and service requirements create new important research problems. First, the high…
Descriptors: Data, Privacy, Information Security, Data Analysis
Yan, Yilin – ProQuest LLC, 2018
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…
Descriptors: Information Science, Information Retrieval, Multimedia Materials, Data
Tyagi, Himanshu – ProQuest LLC, 2013
This dissertation concerns the secure processing of distributed data by multiple terminals, using interactive public communication among themselves, in order to accomplish a given computational task. In the setting of a probabilistic multiterminal source model in which several terminals observe correlated random signals, we analyze secure…
Descriptors: Computation, Correlation, Computers, Data Processing
Aksut, Ann Ahu – ProQuest LLC, 2013
Numerous organizations collect and distribute non-aggregate personal data for a variety of different purposes, including demographic and public health research. In these situations, the data distributor is responsible with the protection of the anonymity and personal information of individuals. Microaggregation is one of the most commonly used…
Descriptors: Data Collection, Data Analysis, Multivariate Analysis, Disclosure
Casstevens, Randy M. – ProQuest LLC, 2013
Innovation processes are critical for preserving and improving our standard of living. While innovation has been studied by many disciplines, the focus has been on qualitative measures that are specific to a single technological domain. I adopt a quantitative approach to investigate underlying regularities that generalize across multiple domains.…
Descriptors: Innovation, Computation, Models, Social Sciences
Wimmer, Hayden – ProQuest LLC, 2013
A large body of literature exists on evolutionary computing, genetic algorithms, decision trees, codified knowledge, and knowledge management systems; however, the intersection of these computing topics has not been widely researched. Moving through the set of all possible solutions--or traversing the search space--at random exhibits no control…
Descriptors: Knowledge Management, Management Systems, Mathematics, Computation
Orcan, Fatih – ProQuest LLC, 2013
Parceling is referred to as a procedure for computing sums or average scores across multiple items. Parcels instead of individual items are then used as indicators of latent factors in the structural equation modeling analysis (Bandalos 2002, 2008; Little et al., 2002; Yang, Nay, & Hoyle, 2010). Item parceling may be applied to alleviate some…
Descriptors: Structural Equation Models, Evaluation Methods, Simulation, Sample Size
Duan, Lian – ProQuest LLC, 2012
Finding the most interesting correlations among items is essential for problems in many commercial, medical, and scientific domains. For example, what kinds of items should be recommended with regard to what has been purchased by a customer? How to arrange the store shelf in order to increase sales? How to partition the whole social network into…
Descriptors: Correlation, Measurement, Measurement Techniques, Measurement Objectives
St. Clair, Suzanne W. – ProQuest LLC, 2011
The current study evaluated the performance of traditional versus modern MDTs in the estimation of fixed-effects and variance components for data missing at the second level of an hierarchical linear model (HLM) model across 24 different study conditions. Variables manipulated in the analysis included, (a) number of Level-2 variables with missing…
Descriptors: Hierarchical Linear Modeling, Data Analysis, Sample Size, Computation
Heien, Christopher Harris – ProQuest LLC, 2012
Information Product Maps are visual diagrams used to represent the inputs, processing, and outputs of data within an Information Manufacturing System. A data unit, drawn as an edge, symbolizes a grouping of raw data as it travels through this system. Processes, drawn as vertices, transform each data unit input into various forms prior to delivery…
Descriptors: Maps, Visual Aids, Information Systems, Quality Assurance
Baydogan, Mustafa Gokce – ProQuest LLC, 2012
Temporal data are increasingly prevalent and important in analytics. Time series (TS) data are chronological sequences of observations and an important class of temporal data. Fields such as medicine, finance, learning science and multimedia naturally generate TS data. Each series provide a high-dimensional data vector that challenges the learning…
Descriptors: Mathematical Models, Multivariate Analysis, Statistical Data, Computation
Kuksa, Pavel – ProQuest LLC, 2011
Analysis of large-scale sequential data has become an important task in machine learning and pattern recognition, inspired in part by numerous scientific and technological applications such as the document and text classification or the analysis of biological sequences. However, current computational methods for sequence comparison still lack…
Descriptors: Data Analysis, Computation, Mathematics, Methods
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