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Articles 451 - 480 of 1308
Full-Text Articles in Statistical Models
Modeling Longitudinal Change In Cervical Length Across Pregnancy, Hope M. Wolf, Shawn J. Latendresse, Jerome F. Strauss Iii, Timothy P. York
Modeling Longitudinal Change In Cervical Length Across Pregnancy, Hope M. Wolf, Shawn J. Latendresse, Jerome F. Strauss Iii, Timothy P. York
Graduate Research Posters
Introduction: A short cervix (cervical length < 25 mm) in the mid-trimester (18 to 24 weeks) of pregnancy is a powerful predictor of spontaneous preterm delivery (gestational age at delivery < 37 weeks). Although the biological mechanisms of cervical remodeling have been the subject of extensive investigation, very little is known about the rate of change in cervical length over the course of a pregnancy, or the extent to which rapid cervical shortening increases maternal risk for spontaneous preterm delivery.
Methods: A cohort of 5,160 unique women carrying 5,971 singleton pregnancies provided two or more measurements of cervical length during pregnancy. Cervical length was measured in millimeters using a transvaginal 12-3 MHz ultrasound endocavity probe (SuperSonic Imagine). Maternal characteristics, including relevant medical history and birth outcome data, were collected for each participant. Gestational age at delivery was measured from the first day of each woman’s last menstrual period and confirmed by ultrasound. Repeated measurements of cervical length during pregnancy were modeled as a longitudinal, multilevel growth curve in MPlus. A three-level variance structure was …
Modified Firearm Discharge Residue Analysis Utilizing Advanced Analytical Techniques, Complexing Agents, And Quantum Chemical Calculations, William J. Feeney
Modified Firearm Discharge Residue Analysis Utilizing Advanced Analytical Techniques, Complexing Agents, And Quantum Chemical Calculations, William J. Feeney
Graduate Theses, Dissertations, and Problem Reports (ETD)
The use of gunshot residue (GSR) or firearm discharge residue (FDR) evidence faces some challenges because of instrumental and analytical limitations and the difficulties in evaluating and communicating evidentiary value. For instance, the categorization of GSR based only on elemental analysis of single, spherical particles is becoming insufficient because newer ammunition formulations produce residues with varying particle morphology and composition. Also, one common criticism about GSR practitioners is that their reports focus on the presence or absence of GSR in an item without providing an assessment of the weight of the evidence. Such reports leave the end-used with unanswered questions, …
Statistical Methods In Genetic Studies, Cheng Gao
Statistical Methods In Genetic Studies, Cheng Gao
Dissertations, Master's Theses and Master's Reports
This dissertation includes three Chapters. A brief description of each chapter is organized as follows.
In Chapter 1, we proposed a new method, called MF-TOWmuT, for genome-wide association studies with multiple genetic variants and multiple phenotypes using family samples. MF-TOWmuT uses kinship matrix to account for sample relatedness. It is worth mentioning that in simulations, we considered hidden polygenic effects and varied the proportion of variance contributed by it to generate phenotypes. Simulation studies show that MF-TOWmuT can preserve the type I error rates and is more powerful than several existing methods in different simulation scenarios, MFTOWmuT is also quite …
Bayesian Techniques For Relating Genetic Polymorphisms To Diffusion Tensor Images Of Cocaine Users, Tmader Alballa
Bayesian Techniques For Relating Genetic Polymorphisms To Diffusion Tensor Images Of Cocaine Users, Tmader Alballa
Theses and Dissertations
Past investigations utilizing Diffusion Tensor Imaging (DTI) have demonstrated that cocaine use disorder (CUD) yields white matter changes. We proposed three Bayesian techniques in order to explore the relationship between Fractional Anisotropy (FA), genetic data, and years of cocaine use (YCU). CUD participants exhibit abnormality in different areas of the brain versus non-drug using controls, which is measured by DTI. This dissertation is motivated by a neuroimaging genetic study in cocaine dependence, which found that there were relationships between several genes such as GAD and 5-HT2R and CUD subjects.
In the first chapter, there is background on the …
Modeling Multivariate Hopfield-Transformer Hawkes Process: Application To Sovereign Credit Default Swaps, Mohsen Bahremani
Modeling Multivariate Hopfield-Transformer Hawkes Process: Application To Sovereign Credit Default Swaps, Mohsen Bahremani
Theses and Dissertations (Comprehensive)
Hawkes process was evolved so that the past events contribute to the occurrence time of future events by self-exciting or mutually exciting. However, many real-world data do not follow the Hawkes process's assumptions (i.e., positivity, additivity, and exponential decay) and become more complex to be modeled by the traditional Hawkes processes, so the neural Hawkes process was developed to tackle the challenges. However, Recurrent Neural Networks (RNN) fail to capture long-term dependencies among multiple point processes, and Transformer Hawkes processes only address temporal characteristics of Hawkes processes. In this thesis, we proposed a combination of neural networks and Hawkes processes …
Multi-Level Small Area Estimation Based On Calibrated Hierarchical Likelihood Approach Through Bias Correction With Applications To Covid-19 Data, Nirosha Rathnayake
Multi-Level Small Area Estimation Based On Calibrated Hierarchical Likelihood Approach Through Bias Correction With Applications To Covid-19 Data, Nirosha Rathnayake
Theses & Dissertations
Small area estimation (SAE) has been widely used in a variety of applications to draw estimates in geographic domains represented as a metropolitan area, district, county, or state. The direct estimation methods provide accurate estimates when the sample size of study participants within each area unit is sufficiently large, but it might not always be realistic to have large sample sizes of study participants when considering small geographical regions. Meanwhile, high dimensional socio-ecological data exist at the community level, providing an opportunity for model-based estimation by incorporating rich auxiliary information at the individual and area levels. Thus, it is critical …
Influence Of Some Climatic Elements On Radon Concentration In Saeva Dupka Cave, Bulgaria, Peter Nojarov, Petar Stefanov, Karel Turek
Influence Of Some Climatic Elements On Radon Concentration In Saeva Dupka Cave, Bulgaria, Peter Nojarov, Petar Stefanov, Karel Turek
International Journal of Speleology
This study reveals the influence of some climatic elements on radon concentration in Saeva Dupka Cave, Bulgaria. The research is based mainly on statistical methods. Radon concentration in the cave is determined by two main mechanisms. The first one is through penetration of radon from soil and rocks around the cave (present all year round, but has leading role during the warm half of the year). The second one is through thermodynamic exchange of air between inside of the cave and outside atmosphere (cold half of the year). Climatic factors that affect radon concentration in the cave are temperatures (air, …
Gene Set Testing By Distance Correlation, Sho-Hsien Su
Gene Set Testing By Distance Correlation, Sho-Hsien Su
Graduate Theses and Dissertations
Pathways are the functional building blocks of complex diseases such as cancers. Pathway-level studies may provide insights on some important biological processes. Gene set test is an important tool to study the differential expression of a gene set between two groups, e.g., cancer vs normal. The differential expression of a gene set could be due to the difference in mean, variability, or both. However, most existing gene set tests only target the mean difference but overlook other types of differential expression. In this thesis, we propose to use the recently developed distance correlation for gene set testing. To assess the …
Statistical Approaches Of Gene Set Analysis With Quantitative Trait Loci For High-Throughput Genomic Studies., Samarendra Das
Statistical Approaches Of Gene Set Analysis With Quantitative Trait Loci For High-Throughput Genomic Studies., Samarendra Das
Electronic Theses and Dissertations
Recently, gene set analysis has become the first choice for gaining insights into the underlying complex biology of diseases through high-throughput genomic studies, such as Microarrays, bulk RNA-Sequencing, single cell RNA-Sequencing, etc. It also reduces the complexity of statistical analysis and enhances the explanatory power of the obtained results. Further, the statistical structure and steps common to these approaches have not yet been comprehensively discussed, which limits their utility. Hence, a comprehensive overview of the available gene set analysis approaches used for different high-throughput genomic studies is provided. The analysis of gene sets is usually carried out based on …
A Management Strategy Evaluation Of The Impacts Of Interspecific Competition And Recreational Fishery Dynamics On Vermilion Snapper (Rhomboplites Aurorubens) In The Gulf Of Mexico, Megumi C. Oshima
Dissertations
In the Gulf of Mexico (GOM), Vermilion Snapper (Rhomboplites auroruben), are believed to compete with Red Snapper directly for prey and habitat. The two species share similar diets and have significant spatial overlap in the Gulf. Red Snapper are thought to be the dominate competitor, forcing Vermilion Snapper to feed on less nutritious prey when local resources are depleted. In addition to ecological pressures, GOM Vermilion Snapper support substantial commercial and recreational fisheries. Over the past decade, recreational landings have steadily increased, reaching a historical high in 2018. One cause may be stricter regulations for similar target species such as …
Quantifying The Simultaneous Effect Of Socio-Economic Predictors And Build Environment On Spatial Crime Trends, Alfieri Daniel Ek
Quantifying The Simultaneous Effect Of Socio-Economic Predictors And Build Environment On Spatial Crime Trends, Alfieri Daniel Ek
Graduate Theses and Dissertations
Proper allocation of law enforcement agencies falls under the umbrella of risk terrainmodeling (Caplan et al., 2011, 2015; Drawve, 2016) that primarily focuses on crime prediction and prevention by spatially aggregating response and predictor variables of interest. Although mental health incidents demand resource allocation from law enforcement agencies and the city, relatively less emphasis has been placed on building spatial models for mental health incidents events. Analyzing spatial mental health events in Little Rock, AR over 2015 to 2018, we found evidence of spatial heterogeneity via Moran’s I statistic. A spatial modeling framework is then built using generalized linear models, …
Development Of A Statistical Model To Predict Materials’ Unit Prices For Future Maintenance And Rehabilitation In Highway Life Cycle Cost Analysis, Changmo Kim, Ghazan Khan, Brent Nguyen, Emily L. Hoang
Development Of A Statistical Model To Predict Materials’ Unit Prices For Future Maintenance And Rehabilitation In Highway Life Cycle Cost Analysis, Changmo Kim, Ghazan Khan, Brent Nguyen, Emily L. Hoang
Mineta Transportation Institute
The main objectives of this study are to investigate the trends in primary pavement materials’ unit price over time and to develop statistical models and guidelines for using predictive unit prices of pavement materials instead of uniform unit prices in life cycle cost analysis (LCCA) for future maintenance and rehabilitation (M&R) projects. Various socio-economic data were collected for the past 20 years (1997–2018) in California, including oil price, population, government expenditure in transportation, vehicle registration, and other key variables, in order to identify factors affecting pavement materials’ unit price. Additionally, the unit price records of the popular pavement materials were …
Incorporating Shear Resistance Into Debris Flow Triggering Model Statistics, Noah J. Lyman
Incorporating Shear Resistance Into Debris Flow Triggering Model Statistics, Noah J. Lyman
Master's Theses
Several regions of the Western United States utilize statistical binary classification models to predict and manage debris flow initiation probability after wildfires. As the occurrence of wildfires and large intensity rainfall events increase, so has the frequency in which development occurs in the steep and mountainous terrain where these events arise. This resulting intersection brings with it an increasing need to derive improved results from existing models, or develop new models, to reduce the economic and human impacts that debris flows may bring. Any development or change to these models could also theoretically increase the ease of collection, processing, and …
Stochastic Analysis And Statistical Inference For Seir Models Of Infectious Diseases, Andrés Ríos-Gutiérrez, Viswanathan Arunachalam, Anuj Mubayi
Stochastic Analysis And Statistical Inference For Seir Models Of Infectious Diseases, Andrés Ríos-Gutiérrez, Viswanathan Arunachalam, Anuj Mubayi
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Stochastic Modeling Of Ovarian Follicle Growth In Adult Female Rats, Zhaozhi Li
Stochastic Modeling Of Ovarian Follicle Growth In Adult Female Rats, Zhaozhi Li
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Interval Estimation Of Proportion Of Second-Level Variance In Multi-Level Modeling, Steven Svoboda
Interval Estimation Of Proportion Of Second-Level Variance In Multi-Level Modeling, Steven Svoboda
The Nebraska Educator: A Student-Led Journal
Physical, behavioral and psychological research questions often relate to hierarchical data systems. Examples of hierarchical data systems include repeated measures of students nested within classrooms, nested within schools and employees nested within supervisors, nested within organizations. Applied researchers studying hierarchical data structures should have an estimate of the intraclass correlation coefficient (ICC) for every nested level in their analyses because ignoring even relatively small amounts of interdependence is known to inflate Type I error rate in single-level models. Traditionally, researchers rely upon the ICC as a point estimate of the amount of interdependency in their data. Recent methods utilizing an …
Cost Estimating Using A New Learning Curve Theory For Non-Constant Production Rates, Dakotah Hogan, John J. Elshaw, Clay M. Koschnick, Jonathan D. Ritschel, Adedeji B. Badiru, Shawn M. Valentine
Cost Estimating Using A New Learning Curve Theory For Non-Constant Production Rates, Dakotah Hogan, John J. Elshaw, Clay M. Koschnick, Jonathan D. Ritschel, Adedeji B. Badiru, Shawn M. Valentine
Faculty Publications
Traditional learning curve theory assumes a constant learning rate regardless of the number of units produced. However, a collection of theoretical and empirical evidence indicates that learning rates decrease as more units are produced in some cases. These diminishing learning rates cause traditional learning curves to underestimate required resources, potentially resulting in cost overruns. A diminishing learning rate model, namely Boone’s learning curve, was recently developed to model this phenomenon. This research confirms that Boone’s learning curve systematically reduced error in modeling observed learning curves using production data from 169 Department of Defense end-items. However, high amounts of variability in …
A Differential Geometry-Based Machine Learning Algorithm For The Brain Age Problem, Justin Asher, Khoa Tan Dang, Maxwell Masters
A Differential Geometry-Based Machine Learning Algorithm For The Brain Age Problem, Justin Asher, Khoa Tan Dang, Maxwell Masters
The Journal of Purdue Undergraduate Research
No abstract provided.
Predicting Postoperative Delirium Risk For Intracranial Surgery: A Statistical Machine Learning Approach, Juliet Aygun, Alaina Bartfeld, Sahana Rayan
Predicting Postoperative Delirium Risk For Intracranial Surgery: A Statistical Machine Learning Approach, Juliet Aygun, Alaina Bartfeld, Sahana Rayan
The Journal of Purdue Undergraduate Research
No abstract provided.
Machine Learning Approaches For Improving Prediction Performance Of Structure-Activity Relationship Models, Gabriel Idakwo
Machine Learning Approaches For Improving Prediction Performance Of Structure-Activity Relationship Models, Gabriel Idakwo
Dissertations
In silico bioactivity prediction studies are designed to complement in vivo and in vitro efforts to assess the activity and properties of small molecules. In silico methods such as Quantitative Structure-Activity/Property Relationship (QSAR) are used to correlate the structure of a molecule to its biological property in drug design and toxicological studies. In this body of work, I started with two in-depth reviews into the application of machine learning based approaches and feature reduction methods to QSAR, and then investigated solutions to three common challenges faced in machine learning based QSAR studies.
First, to improve the prediction accuracy of learning …
A Geochemical And Statistical Investigation Of The Big Four Springs Region In Southern Missouri, Jordan Jasso Vega
A Geochemical And Statistical Investigation Of The Big Four Springs Region In Southern Missouri, Jordan Jasso Vega
Graduate Theses/Dissertations
The Big Four Springs region hosts four major first-order magnitude springs in southern Missouri and northern Arkansas. These springs are Big Spring (Carter County, MO), Greer Spring (Oregon County, MO), Mammoth Spring (Fulton County, AR), and Hodgson Mill Spring (Ozark County, MO). Based on historic dye traces and hydrogeological investigations, these springs drain an area of approximately 1500 square miles and collectively discharge an average of 780 million gallons of water per day. The rocks from youngest to oldest that are found in Big Four Springs region are the Cotter and Jefferson City Dolomite (Ordovician), Roubidoux Formation (Ordovician), Gasconade Dolomite …
Data Mining For Structural Damage Identification Using Hybrid Artificial Neural Network Based Algorithm For Beam And Slab Girder, Gordan Meisam
Data Mining For Structural Damage Identification Using Hybrid Artificial Neural Network Based Algorithm For Beam And Slab Girder, Gordan Meisam
Student Works (2020-2029)
One of the approaches for structural health monitoring (SHM) consists of two major components, i.e. a network of sensors to collect the response data and an extraction method to obtain information on the structural health condition. Data mining (DM) is a novel data extraction technology which can employ for development of inverse analysis. Implementation of DM techniques in different areas of civil engineering has recently given very good results. However, application of DM in SHM is not used as much as expected, thus, many challenges are still ahead. Therefore, it is necessary to develop the applicability of DM in SHM. …
D-Vine Pair-Copula Models For Longitudinal Binary Data, Huihui Lin
D-Vine Pair-Copula Models For Longitudinal Binary Data, Huihui Lin
Mathematics & Statistics Theses & Dissertations
Dependent longitudinal binary data are prevalent in a wide range of scientific disciplines, including healthcare and medicine. A popular method for analyzing such data is the multivariate probit (MP) model. The motivation for this dissertation stems from the fact that the MP model fails even the binary correlations are within the feasible range. The reason being the underlying correlation matrix of the latent variables in the MP model may not be positive definite. In this dissertation, we study alternatives that are based on D-vine pair-copula models. We consider both the serial dependence modeled by the first order autoregressive (AR(1)) and …
Lectures On Mathematical Computing With Python, Jay Gopalakrishnan
Lectures On Mathematical Computing With Python, Jay Gopalakrishnan
PDXOpen: Open Educational Resources
This open resource is a collection of class activities for use in undergraduate courses aimed at teaching mathematical computing, and computational thinking in general, using the python programming language. It was developed for a second-year course (MTH 271) revamped for a new undergraduate program in data science at Portland State University. The activities are designed to guide students' use of python modules effectively for scientific computation, data analysis, and visualization.
Adopt/Adapt
If you are an instructor adopting or adapting this open educational resource, please help us understand your use by filling out this form
Statistical Methodology To Establish A Benchmark For Evaluating Antimicrobial Resistance Genes Through Real Time Pcr Assay, Enakshy Dutta
Statistical Methodology To Establish A Benchmark For Evaluating Antimicrobial Resistance Genes Through Real Time Pcr Assay, Enakshy Dutta
Department of Statistics: Dissertations, Theses, and Student Research
Novel diagnostic tests are usually compared with gold standard tests for evaluating diagnostic accuracy. For assessing antimicrobial resistance (AMR) to bovine respiratory disease (BRD) pathogens, phenotypic broth microdilution method is used as gold standard (GS). The objective of the thesis is to evaluate the optimal cycle threshold (Ct) generated by real-time polymerase chain reaction (rtPCR) to genes that confer resistance that will translate to the phenotypic classification of AMR. Data from two different methodologies are assessed to identify Ct that will discriminate between resistance (R) and susceptibility (S). First, the receiver operating characteristic (ROC) curve was used to determine the …
Italian Sociologists: A Community Of Disconnected Groups, Aliakbar Akbaritabar, Vincent Traag, Alberto Caimo, Flaminio Squazzoni
Italian Sociologists: A Community Of Disconnected Groups, Aliakbar Akbaritabar, Vincent Traag, Alberto Caimo, Flaminio Squazzoni
Articles
Examining coauthorship networks is key to study scientific collaboration patterns and structural characteristics of scientific communities. Here, we studied coauthorship networks of sociologists in Italy, using temporal and multi-level quantitative analysis. By looking at publications indexed in Scopus, we detected research communities among Italian sociologists. We found that Italian sociologists are fractured in many disconnected groups. The giant connected component of the Italian sociology could be split into five main groups with a mixture of three main disciplinary topics: sociology of culture and communication (present in two groups), economic sociology (present in three groups) and general sociology (present in three …
Working Children On Java Island 2017, Yuniarti
Working Children On Java Island 2017, Yuniarti
International Programs
Children's wellbeing has currently become a global concern as many of them are engaged in the labor force. A small area estimation (SAE) technique, EBLUP under Fey Herriot model, is employed to reveal their number in regencies of Java Island. Statistics have been disaggregated by geographical location (urban/rural) and gender. These statistics are required by the government as the basis for policy making.
Mathematical Modeling: Instructor And Student Resources, Marnie Phipps, Patty Wagner
Mathematical Modeling: Instructor And Student Resources, Marnie Phipps, Patty Wagner
Mathematics Ancillary Materials
This collection of student and instructor materials for Mathematical Modeling contains lesson plans, lecture slides, homework, learning goals, and student notes for the following major topics:
- Linear Functions
- Quadratic Functions
- Exponential Functions
- Logarithmic Functions
This is a materials update for a collection of materials created for a Round Nine ALG Textbook Transformation Grant.
Structural Analysis Of The Multifunctional Spoiie Regulatory Protein Of Clostridioides Difficile., Blythe Emily Bunkers
Structural Analysis Of The Multifunctional Spoiie Regulatory Protein Of Clostridioides Difficile., Blythe Emily Bunkers
Graduate Theses and Dissertations
Clostridioides (formally Clostridium) difficile is a medically relevant pathogen pertinent to infectious disease research. C. difficile is distinctly known for its ability to produce two toxins, enterotoxin A and cytotoxin B, and the propensity to colonize the mammalian gastrointestinal tract. It is known that metabolism is tightly correlated with sporulation in endospore producers such as C. difficile, but an interesting and novel regulatory relationship found by the Ivey lab has yet to be understood. The relationship explored in this study is observed between the sporulation factor, SpoIIE, which represses expression of an ABC peptide transporter, app. In this study, two …
Constitutive Model Of Lateral Unloading Creep Of Soft Soil Under Excess Pore Water Pressure, Wei Huang, Kejun Wen, Xiaojia Deng, Junjie Li, Zhijian Jiang, Yang Li, Lin Li, Farshad Amini
Constitutive Model Of Lateral Unloading Creep Of Soft Soil Under Excess Pore Water Pressure, Wei Huang, Kejun Wen, Xiaojia Deng, Junjie Li, Zhijian Jiang, Yang Li, Lin Li, Farshad Amini
Civil and Architectural Engineering Faculty Research
Presented in this paper is a study on the lateral unloading creep tests under different excess pore water pressures. The marine sedimentary soft soil in Shenzhen, China, was selected in this study. The results show that the excess pore water pressure plays a significant role in enhancing the unloading creep of soft soil. Higher excess pore water pressure brings more obvious creep deformation of soft soil and lower ultimate failure load. Meanwhile, the viscoelastic and the viscoplastic modulus of soft soil were found to exponentially decline with creep time. A modified merchant model and a combined model of the modified …